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IBM Switch 15 User's Manual

1. GLOBAL_MEAN 155 GLOBAL_MIN 155 GLOBAL_SDEV 155 GLOBAL_SUM 55 handling missing values 102 in CLEM expressions 120 PARTITION 157 PREDICTED I 17 157 TARGET 17 1157 user defined functions UDFs 120 generated models palette 19 global functions 155 global values in CLEM expressions 121 graphs adding to projects 202 saving output 89 greater than operator 135 grouping symbol number display formats 56 hasendstring function 41 hasmidstring function 141 hasstartstring function 41 hassubstring function 141 hints general usage 96 host name IBM SPSS Modeler Server 3HI4 hot keys 26 HTML output screen reader 245 IBM InfoSphere Warehouse ISW PMML export IBM SPSS Collaboration and Deployment Services IBM SPSS Collaboration and Deployment Services Enterprise View 160 185 IBM SPSS Collaboration and Deployment Services Repository 158 160 browsing 162 connecting to 16I deleting objects and versions 178 folders I77 179 locking and unlocking objects 177 object properties 80 retrieving objects 172 searching in 175 single sign on 61 storing objects 164 transferring projects to 204 IBM SPSS Modeler I 17 acces
2. Format Examples HHMMSS 120112 010101 221212 HHMM 1223 0745 2207 MMSS 5558 0100 HH MM SS 12 01 12 01 01 01 22 12 12 HH MM 12 23 07 45 22 07 MM SS 55 58 01 00 H H M M S S 12 1 12 1 1 1 22 12 12 H H M M 12 23 7 45 22 7 M M S S 55 58 1 0 HH MM SS 12 01 12 01 01 01 22 12 12 HH MM 12 23 07 45 22 07 131 CLEM Language Reference Format Examples MM SS 55 58 01 00 H H M M S S 12 1 12 1 1 1 22 12 12 H H M M 12 23 7 45 22 7 M M S S 55 58 1 0 CLEM Operators The following operators are available Operation Comments Precedence see next section or Used between two CLEM expressions Returns a value of true if either is true or if both are true 10 and Used between two CLEM expressions Returns a value of true if both are true Used between any two comparable items Returns true if ITEM is equal to ITEM2 Identical to Used between any two comparable items Returns true if ITEM is not equal to ITEM2 Identical to Used between any two comparable items Returns true if ITEM is strictly greater than ITEM2 Used between any two comparable items Returns true if ITEM is greater than or equal to ITEM2 Used between any two comparable items Returns true if ITEM1 is strictly less than ITEM2 Used between any two comparable items Returns true if ITEM is le
3. enable nodes 46 encoding 56 248 endstring function 41 Enterprise View node 185 equals operator 135 error messages essential fields D1 04 Evaluation node performance 234 examples Applications Guide 4 overview 5 execution times viewing 7 exponential function 138 exporting PMML 196 198 stream descriptions 77 Expression Builder accessing 119 finding and replacing text 123 overview 117 using L19 expressions 127 f distribution probability functions 39 factor Feature Selection node missing values 01 FIELD function 102 157 fields 29 127 T29 in CLEM expressions 121 viewing values FIELDS_BETWEEN function 102 115 157 FIELDS_MATCHING function 102 115 157 filler node missing values 102 finding text 123 first_index function I17 135 first_non_null function 17 35 first_non_null_index function 117 135 folders IBM SPSS Collaboration and Deployment Services Repository 177 79 fonts 220 fracof function 138 functions 129 4130 33H134 150 BLANK database 120 examples 108 FIELD 117 157 GLOBAL_MAX 55
4. logging in to IBM SPSS Modeler Server 13 logical functions 137 logistic regression 245 export as PMML 222 lowertoupper function 41 machine learning 29 main window 18 managers 19 mandatory fields D5 mapping data 94 mapping fields PT matches function T41 max function 135 MAX function 52 MAX function 150 152 max_index function 117 135 117 am 84 tion and Deployment 177 63 max_n function 15 135 256 Index MEAN function 50 152 MEAN function 150 152 mean_n function 115 38 member function 1135 memory managing 215 216 Merge node performance messages displaying generated SQL middle mouse button simulating 26 43 min function 135 MIN function 152 MIN function 150 152 min_index function min_n function 115 K7 135 135 minimizing 23 missing values 101 113 CLEM expressions 102 filling handling in records 101 mod function 138 model nuggets 78 model refresh 185 modeling branch 78 modeling nodes B4 modeling palette tab customization 228 performance 234 models 78
5. palette tab customization palettes 13 customizing 223 parallel processing enabling 60 parameters in CLEM expressions 121 model building 188 runtime prompts 70 scoring 188 session 68 70 112 stream 68 70 12 type 70 using in scenarios I PARTITION_FIELD function 157 password IBM SPSS Modeler Server 13 paste 21 performance CLEM expressions 234 node caching 50 231 of modeling nodes 234 of process nodes 233 period 56 Index pi function 139 PMML export options 221 exporting models 196 198 importing models 197198 PMML models linear regression logistic regression port number IBM SPSS Modeler Server 3HI4 power exponential function 138 PowerPoint files 202 precedence 3 PREDICTED function 157 Predictive Applications 85 preview node data 52 printing 27 streams 24 48 probability functions 139 process nodes 42 performance projects 20 200 adding objects annotating 206 building Classes view 202 closing 209 creating new 202 CRISP DM view 20 folder properties 207 generating reports in the IBM SPSS Collaboration and Deployment Services Repository 204 object properties setting a default folder 201 setting properties storing in the IBM SPSS Collaboration and Deployment Services Reposit
6. adding to projects exporting 22 refreshing 190 replacing 219 storing in the IBM SPSS Collaboration and Deployment 2 Services Repository 172 models palette 172 mouse using in IBM SPSS Modeler 26 43 MULTIL_RESPONSE_SET function b 117 gt 157 multiple IBM SPSS Modeler sessions multiple category sets in CLEM expressions 117 multiple dichotomy sets in CLEM expressions IT7 multiple response sets in CLEM expressions I17 121 naming nodes and streams 86 navigating keyboard shortcuts 233 negate function 38 neural net node large sets 57 Neural Net node performance 234 new features 7 L0 node caching enabling 50 231 node names 86 node palette selection 225 nodes 12 adding 43 46 adding comments to 78 adding to projects 202H203 annotating 78 86 bypassing in a stream 45 connecting in a stream 43 custom palette creation 225 custom subpalette creation 227 data preview 52 deleting 3 deleting connections 47 disabling 46 48 disabling in a stream 46 displaying on palette 225 duplicating 48 editing 48 enabling 46 execution times 67 introduction 2 loading 90 locking 53 order of palette tab customization performance 233 234 previewing data removing from palette 225 saving 88 searching for 73 settin
7. OFFSET ValueCategory 1 Else D Ee CLEM Examples To illustrate correct syntax as well as the types of expressions possible with CLEM example expressions follow Simple Expressions Formulas can be as simple as this one which derives a new field based on the values of the fields After and Before After Before Before 100 0 Notice that field names are unquoted when referring to the values of the field Similarly the following expression simply returns the log of each value for the field salary log salary 109 Building CLEM Expressions Complex Expressions Expressions can also be lengthy and more complex The following expression returns true if the value of two fields KX Kohonen and KY Kohonen fall within the specified ranges Notice that here the field names are single quoted because the field names contain special characters KX Kohonen gt 0 2635771036148072 and KX Kohonen lt 0 3146203637123107 and KY Kohonen gt 0 18975617885589602 and KY Kohonen lt 0 17674794197082522 gt T Several functions such as string functions require you to enter several parameters using correct syntax In the following example the function subscrs is used to return the first character of a produce_ID field indicating whether an item is organic genetically modified or conventional The results of an expression are described by gt result subscrs 1 produce_ID
8. 0 c ce ccc te eee n eee n tenes Performance Modeling Nodes 0 ccc ccc eee ene e tent n eens Performance CLEM Expressions 0 0 cece cee cece tenet teen eens Appendices A Accessibility in IBM SPSS Modeler 236 Overview of Accessibility in IBM SPSS Modeler 00 0 0 c cece eee een eens Types of Accessibility SUpport s sss irris etn etn eens Accessibility for the Visually Impaired 0 0 0 0 0 cee eens Accessibility for Blind Users 0 000 cece ttt tenes Keyboard Accessibility 2 0 0 cence ene n tenn nes Using a Screen Reader 1 eee n eet n eens TIPSA0USE 54 ch vey oath op cha aea i Eide Ha hat heeled as bee da aa ai a a ds Interference with Other Software 0 cc ccc cece ete e enn JAWS and JIVI sidan u iin is kee e d eee Cote Deo an dew dT NENES dee eae dd an Using Graphs in IBM SPSS Modeler 0 0 0c cece eect eens B Unicode Support 248 Unicode Support in IBM SPSS Modeler 00 0 c eect eet C Notices Index Chapter L About IBM SPSS Modeler IBM SPSS Modeler is a set of data mining tools that enable you to quickly develop predictive models using business expertise and deploy them into business operations to improve decision making Designed around the industry standard CRISP DM model SPSS Modeler supports the entire data mining process from data to better business results SPSS Modeler offers a variety of modeling methods taken from
9. Chapter 5 vY v Vv v Yy Note The following databases support temporary tables for the purpose of caching DB2 Netezza Oracle SQL Server and Teradata Other databases will use a normal table for database caching The SQL code can be customized for specific databases contact Support for assistance To Flush a Cache A white document icon on a node indicates that its cache is empty When the cache is full the document icon becomes solid green If you want to replace the contents of the cache you must first flush the cache and then re run the data stream to refill it On the stream canvas right click the node and click Cache on the menu On the caching submenu click Flush To Save a Cache You can save the contents of a cache as an IBM SPSS Statistics data file sav You can then either reload the file as a cache or you can set up a node that uses the cache file as its data source You can also load a cache that you saved from another project On the stream canvas right click the node and click Cache on the menu On the caching submenu click Save Cache In the Save Cache dialog box browse to the location where you want to save the cache file Enter a name in the File Name text box Be sure that sav is selected in the Files of Type list and click Save To Load a Cache If you have saved a cache file before removing it from the node you can reload it On the stream canvas right click the node and click Cach
10. M Display execution times Decimal symbol Select either a comma or a period as a decimal separator Grouping symbol For number display formats select the symbol used to group values for example the comma in 3 000 00 Options include none period comma space and locale defined in which case the default for the current locale is used Encoding Specify the stream default method for text encoding Note Applies to Var File source node and Flat File export node only No other nodes use this setting most data files have embedded encoding information You can choose either the system default or UTF 8 The system default is specified in the Windows Control Panel or if running in distributed mode on the server computer For more information see the topic Unicode Support in IBM SPSS Modeler in Appendix B on p 248 Ruleset Evaluation Determines how rule set models are evaluated By default rule sets use Voting to combine predictions from individual rules and determine the final prediction To ensure that rule sets use the first hit rule by default select First Hit Note that this option does not apply to Decision List models which always use the first hit as defined by the algorithm 57 Building Streams Maximum number of rows to show in Data Preview Specify the number of rows to be shown when a preview of the data is requested for a node For more information see the topic Previewing ata in Nodes
11. modelingintro str modelingintro str modelingintro str modelingintro str modelingintro str modelingintro str ISPS SPS SPS SPS SPS SPS SPS SPS admin admin admin admin admin admin admin admin Sep7 Sep 7 Sep 7 Sep 7 Sep7 May 28 Sep 7 May 27 5 4 3 2 1 1 0 0 L EOE AANA SG Name Version Label Created By Modified Date Keywords 176 Chapter 9 When searching for objects by name an asterisk can be used as a wildcard character to match any string of characters and a question mark matches any single character For example cluster matches all objects that include the string cluster anywhere in the name The search string m0 _ matches MOJ_cluster str and MO2_cluster str but not MOla_cluster str Searches are not case sensitive cluster matches Cluster matches CLUSTER Note If the number of objects is large searches may take a few moments Searching by Other Criteria You can perform a search based on title label dates author keywords indexed content or description Only objects that match all specified search criteria will be found For example you could locate all streams containing one or more clustering models that also have a specific label applied and which were modified after a specific date Figure 9 15 Searching for streams containing a specific type of model
12. Building Streams m Logging and status Options controlling SQL logging and record status For more information see the topic Setting SQL logging and record status options for streams on p 63 m Layout Options relating to the layout of the stream on the canvas For more information see the topic Setting layout options for streams on p 64 To Set Stream Options gt On the File menu click Stream Properties or select the stream from the Streams tab in the managers pane right click and then click Stream Properties on the pop up menu gt Click the Options tab Alternatively on the Tools menu click Stream Properties gt Options Setting general options for streams The general options are a set of miscellaneous options that apply to various aspects of the current stream 56 Chapter 5 Figure 5 15 Setting general options for a stream O Stream Select a setting These are general settings that apply to the current stream Click Save As Default to use these settings as the default for all your streams Date Time Number formats Decimal symbol Periodi AuTi Optimization Grouping symbol Noe Logging and Status Encoding System defaut Layout Ruleset Evaluation Maximum number of rows to show in Data Preview Maximum members for nominal fields Fi Limit set size for Kohonen and K Means modeling Refresh source nodes on execution _ Display field and value labels in output
13. The SNA Diffusion Analysis node models the flow of information from a group member to their social environment A group member is assigned an initial weighting which is propagated across the network as a gradually reducing figure This process continues until each member of the network has been assigned a weighting relative to the original group member according to the amount of information that has reached them The individual member scores are then derived directly from these weightings In this way for example a service provider could identify customers that are at a higher risk of churn according to their relationship with a recent churner Chapter 3 IBM SPSS Modeler Overview Getting Started As a data mining application IBM SPSS Modeler offers a strategic approach to finding useful relationships in large data sets In contrast to more traditional statistical methods you do not necessarily need to know what you are looking for when you start You can explore your data fitting different models and investigating different relationships until you find useful information Starting IBM SPSS Modeler To start the application click Start gt All Programs gt IBM SPSS Modeler15 gt IBM SPSS Modeler15 The main window is displayed after a few seconds Figure 3 1 IBM SPSS Modeler main application window File Edit Insert View Tools SuperNode Window Help 2 SHG shes A4O bw EENEN T E Business Under Data Understandi
14. m Look and feel Enables you to choose a standard color scheme and screen design You can choose from SPSS Standard default a design common across IBM SPSS products SPSS Classic a design familiar to users of earlier versions of SPSS Modeler Windows a Windows design that may be useful for increased contrast in the stream canvas and palettes Default font size for nodes Specify a font size to be used in the node palettes and for nodes displayed in the stream canvas Note You can set the size of the node icons for a stream on the Layout pane of the Options tab of the stream properties dialog box From the main menu choose Tools gt Stream Properties gt Options gt Layout Custom Colors This table lists the currently selected colors used for various display items For each of the items listed in the table you can change the current color by double clicking the corresponding row in the Color column and selecting a color from the list To specify a custom color scroll to the bottom of the list and click the Color entry Chart Category Color Order This table lists the currently selected colors used for display in newly created graphs The order of the colors reflects the order in which they will be used in the chart For example if a nominal field used as a color overlay contains four unique values then only the first four colors listed here will be used For each of the items listed in the table you can change the current
15. Storing a Models palette gt Right click the background of the Models palette gt On the pop up menu click Store Palette gt Continue from Completing the storage procedure Completing the storage procedure gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator gt Inthe Repository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 164 Retrieving Objects from the Repository You can retrieve streams models model palettes nodes projects and output objects that have been stored in the repository Note Besides using the menu options as described here you can also retrieve streams output objects models and model palettes by right clicking in the appropriate tab of the managers pane at the top right of the SPSS Modeler window gt To retrieve a stream on the IBM SPSS Modeler main menu click File gt Retrieve Stream gt To retrieve a model model palette project or output object on the SPSS Modeler main menu click File gt Models gt Retrieve Model or File gt Models gt Retrieve Models Palette 173
16. a pm_customer_train2 s Type response response bere ae _ pm_customer_train1 s Type Select response If an error is found the scoring branch is highlighted in the scoring branch error color and an error message is displayed You can set the error color by means of a Custom Color option For more information see the topic Setting Display Options in Chapter 12 on p 220 If an error is found proceed as follows gt Correct the error according to the contents of the error message gt Do one of the following m Right click the terminal node and click Check Scenario on the pop up menu m On the main menu click Tools gt Stream Properties gt Deployment and click Check gt If necessary repeat this process until no errors are found Chapter Exporting to External Applications About Exporting to External Applications IBM SPSS Modeler provides a number of mechanisms to export the entire data mining process to external applications so that the work you do to prepare data and build models can be used to your advantage outside of SPSS Modeler as well The previous section showed how you can deploy streams to an IBM SPSS Collaboration and Deployment Services repository to take advantage of its multi user access job scheduling and other features In a similar way SPSS Modeler streams can also be used in conjunction with IBM SPSS Modeler Advantage m Predictive Applications 5
17. 123 chi square distribution probability functions 139 classes 20 200 202 CLEM 17 building expressions 119 checking expressions 123 datatypes 28H129 examples 108 expressions ITT 127 functions 120 introduction 27 L05 language 127 CLEM expressions finding and replacing text 123 parameters 68 L12 performance 234 CLEM functions bitwise 140 blanks and nulls comparison 135 conversion 135 datetime 146 global 55 information 34 list of available 133 logical 137 missing values 102 numeric I probability 139 random 41 sequence 150 152 special functions 157 string 41 trigonometric 139 client default directory 216 colors setting 220 comma 56 command line starting IBM SPSS Modeler 13 156 252 Index 253 comments keyboard shortcuts 242 listing all in a stream 84 on nodes and streams comparison functions 35 concatenating strings 135 conditions 11 connections server cluster 16 to IBM SPSS Collaboration and Deployment Services Repository I61H162 to IBM SPSS Modeler Server 3HI4 16 conventions 133 conversion functions 135 Coordinator of Processes 16 COP 16 copy 21
18. 141 SUM function 152 SUM function 150 152 sum_n function 115 38 SuperNode parameters 68 112 system options 215 system missing values D9 t distribution probability functions 139 tables adding to projects saving output 89 tan function 139 tanh function 139 TARGET function 157 temp directory 16 template fields 95 templates 92 terminal nodes 42 Index testbit function TESTING_PARTITION function 157 text data files encoding 248 text encoding 56 THIS function 152 THIS function 150 152 time and date functions 129 130 time fields converting 150 time formats 58 129 130 time functions 1294130 time_before 135 1146 time_hours_difference 146 time_in_hours 146 time_in_mins 146 time_in_secs 146 time_mins_difference 146 time_secs_difference 146 time_before function 35 _ tips for accessibility 246 general usage 96 to_date function 135 1146 to_dateline function 146 to_datetime function 135 to_integer function 135 to_number function 135 to_real function 135 to_string function 135 to_time function 135 146 to_
19. Chapter A Understanding Data Mining Data Mining Overview Through a variety of techniques data mining identifies nuggets of information in bodies of data Data mining extracts information in such a way that it can be used in areas such as decision support prediction forecasts and estimation Data is often voluminous but of low value and with little direct usefulness in its raw form It is the hidden information in the data that has value In data mining success comes from combining your or your expert s knowledge of the data with advanced active analysis techniques in which the computer identifies the underlying relationships and features in the data The process of data mining generates models from historical data that are later used for predictions pattern detection and more The technique for building these models is called machine learning or modeling Modeling Techniques IBM SPSS Modeler includes a number of machine learning and modeling technologies which can be roughly grouped according to the types of problems they are intended to solve m Predictive modeling methods include decision trees neural networks and statistical models m Clustering models focus on identifying groups of similar records and labeling the records according to the group to which they belong Clustering methods include Kohonen k means and TwoStep Association rules associate a particular conclusion such as the purchase of a particula
20. Ctrl Up Arrow Used in the node palette to move focus from a node to its palette tab Enter When a node is selected in the node palette including refined models in the generated models palette this keystroke adds the node to the stream canvas Pressing Enter when a node is already selected on the canvas opens the dialog box for that node Ctrl Enter When a node is selected in the palette adds that node to the stream canvas without selecting it and moves focus to the first node in the palette Alt Enter When a node is selected in the palette adds that node to the stream canvas and selects it while moving focus to the first node in the palette Shift Spacebar When a node or comment has focus in the palette toggles between selecting and deselecting that node or comment If any other nodes or comments are also selected this causes them to be deselected Ctrl Shift Spacebar When a node or comment has focus in the stream or a node or comment has focus on the palette toggles between selecting and deselecting the node or comment This does not affect any other selected nodes or comments Left Right Arrow If the stream canvas has focus moves the entire stream horizontally on the screen If a palette tab has focus cycles between tabs If a palette node has focus moves between nodes in the palette Up Down Arrow If the stream canvas has focus moves the entire stream vertically on the scr
21. IBM SPSS Modeler 15 User s Guide lli Ili Te Note Before using this information and the product it supports read the general information under Notices on p 249 This edition applies to IBM SPSS Modeler 15 and to all subsequent releases and modifications until otherwise indicated in new editions Adobe product screenshot s reprinted with permission from Adobe Systems Incorporated Microsoft product screenshot s reprinted with permission from Microsoft Corporation Licensed Materials Property of IBM Copyright IBM Corporation 1994 2012 U S Government Users Restricted Rights Use duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp Preface IBM SPSS Modeler is the IBM Corp enterprise strength data mining workbench SPSS Modeler helps organizations to improve customer and citizen relationships through an in depth understanding of data Organizations use the insight gained from SPSS Modeler to retain profitable customers identify cross selling opportunities attract new customers detect fraud reduce risk and improve government service delivery SPSS Modeler s visual interface invites users to apply their specific business expertise which leads to more powerful predictive models and shortens time to solution SPSS Modeler offers many modeling techniques such as prediction classification segmentation and association detection algorithms Once models are created IBM
22. Kevevords Managing Properties of Repository Objects You can control various object properties from SPSS Modeler You can m View the properties of a folder m View and edit the properties of an object m Create apply and delete version labels for an object Viewing Folder Properties To view properties for any folder in the repository window right click the required folder Click Folder Properties General tab Figure 9 18 Folder properties a Repository Folder Properties Xj Name Buildinfo Created on Thu Jul 12 20 13 23 BST 2007 Last modified Thu Jul 12 20 13 28 BST 2007 e a 180 Chapter 9 Displays the folder name creation and modification dates Permissions tab Specifies read and write permissions for the folder All users and groups with access to the parent folder are listed Permissions follow a hierarchy For example if you do not have read permission you cannot have write permission If you do not have write permission you cannot have delete permission Figure 9 19 Folder properties Repository Folder Properties Users And Groups write Delete everyone Fi Fi Users And Groups Lists the repository users and groups that have at least Read access to this folder Select the Write and Delete check boxes to add those access rights for this folder to a particular user or group Click the Add Users Groups icon on the right side of the Permissions tab to assig
23. Upper h 00 es E re C Type Displays the currently selected measurement level You can change this value to reflect the way that you intend to use the parameter in IBM SPSS Modeler Storage Displays the storage type if known Storage types are unaffected by the measurement level continuous nominal or flag that you choose for work in SPSS Modeler You can alter the storage type on the main Parameters tab The bottom half of the dialog box dynamically changes depending on the measurement level selected in the Type field Continuous Measurement Levels Lower Specify a lower limit for the parameter values Upper Specify an upper limit for the parameter values Labels You can specify labels for any value of a range field Click the Labels button to open a separate dialog box for specifying value labels Nominal Measurement Levels Values This option allows you to specify values for a parameter that will be used as a nominal field Values will not be coerced in the SPSS Modeler stream but will be used in a drop down list for external deployment applications Using the arrow and delete buttons you can modify existing values as well as reorder or delete values Flag Measurement Levels True Specify a flag value for the parameter when the condition is met False Specify a flag value for the parameter when the condition is not met Labels You can specify labels for the values of a flag field Stream Deployme
24. admin Mar 3 2009 10 3 Initial Ma newschancart_ Test SPS admin Feb 26 2009 12 LA Fe F Author F Keywords Name Version Label Created By Modified Date Keywords Object Types You can restrict the search to models streams outputs nodes SuperNodes projects model palettes scenarios or other types of objects m Models You can search for models by category classification approximation clustering etc or by a specific modeling algorithm such as Kohonen You can also search by fields used for example all models that use a field named income as an input or output target field m Streams For streams you can restrict the search by fields used or model type either category or algorithm contained in the stream 177 Using IBM SPSS Modeler with a Repository Topics You can search on models associated with specific topics from a list set by repository users with the appropriate privileges for more information see the Deployment Manager User s Guide To obtain the list check this box then click the Add Topics button that is displayed select one or more topics from the list and click OK Label Restricts the search to specific object version labels Dates You can specify a creation or modification date and search on objects before after or between the specified date range Author Restricts the search to objects created by a specific user Keywords
25. functions cannot be called from scripts Function Result Description Performs an action on all fields specified in FIELD Any the expression context Note that this function cannot be called from a script When a CLEM expression is used in a user defined analysis function TARGET TARGET Any represents the target field or correct value for the target predicted pair being analyzed This function is commonly used in an Analysis node When a CLEM expression is used in a user defined analysis function PREDICTED PREDICTED Any represents the predicted value for the target predicted pair being analyzed This function is commonly used in an Analysis node PARTITION FIELD Any a the name of the current partition Returns the value of the current training partition For example to select training records using a Select node use the CLEM expression TRAINING_PARTITION Any PARTITION_FIELD TRAINING_PARTITION This ensures that the Select node will always work regardless of which values are used to represent each partition in the data TESTING_PARTITION Any Returns the value of the current testing partition VALIDATION_PARTITION Any Returns the value of the current validation partition Returns the list of field names between the specified start and end fields inclusive based on the natural that is insert order of the fields FIELDS_BETWEEN start end Any in the data For more information s
26. After you have created a stream you can save it for future reuse To Save a Stream On the File menu click Save Stream or Save Stream As In the Save dialog box browse to the folder in which you want to save the stream file Enter a name for the stream in the File Name text box Select Add to project if you would like to add the saved stream to the current project Clicking Save stores the stream with the extension str in the specified directory Automatic backup files Each time a stream is saved the previously saved version of the file is automatically preserved as a backup with a hyphen appended to the filename for example mystream str To restore the backed up version simply delete the hyphen and reopen the file Saving States gt gt In addition to streams you can save states which include the currently displayed stream diagram and any model nuggets that you have created listed on the Models tab in the managers pane To Save a State On the File menu click State gt Save State or Save State As In the Save dialog box browse to the folder in which you want to save the state file Clicking Save stores the state with the extension cst in the specified directory Saving Nodes You can also save an individual node by right clicking the node on the stream canvas and clicking Save Node on the pop up menu Use the file extension nod 89 Building Streams Saving Multiple Stream Objects When yo
27. For more information see the topic Opening aj Stream in IBM SPSS Modeler Advantage in Chapter 10 on p 95 Deployment as a scenario enables the stream to be used by Predictive Applications version 5 the predecessor of IBM SPSS Modeler Advantage For more information see Stream Deployment Options on p 185 Requirements for Streams Deployed as Scenarios m To ensure consistent access to enterprise data streams deployed as scenarios must be accessed through the Enterprise View component of IBM SPSS Collaboration and Deployment Services This means that in SPSS Modeler there must be at least one Enterprise View source node within each designated scoring or modeling branch in the stream m To use the Enterprise View node IBM SPSS Collaboration and Deployment Services must be installed configured and accessible from your site with an Enterprise View Application Views and Data Provider Definitions DPDs already defined For more information contact your local administrator or see the corporate website at http www ibm com software analytics spss products deployment cds m A DPD is defined against a particular ODBC data source To use a DPD from SPSS Modeler you must have an ODBC data source defined on the SPSS Modeler server host that has the same name and that connects to the same data store as the one referenced in the DPD m In addition the I BM SPSS Collaboration and Deployment Ser
28. SPSS Statistics For more information about PMML see the Data Mining Group website http www dmg org To Export a Model PMML export is supported for most of the model types generated in SPSS Modeler For more information see the topic Model Types Supporting PMML on p 98 gt Right click a model nugget on the models palette Alternatively double click a model nugget on the canvas and select the File menu gt On the menu click Export PMML Figure 10 1 Exporting a model in PMML format Add To Stream Browse Rename and Annotate Generate Modeling Node Save Model Save Model As Store Model Add to Project X Delete 197 Exporting to External Applications gt In the Export or Save dialog box specify a target directory and a unique name for the model Note You can change options for PMML export in the User Options dialog box On the main menu click Tools gt Options gt User Options and click the PMML tab For more information see the topic Setting PMML Export Options in Chapter 12 on p 221 To Import a Model Saved as PMML Models exported as PMML from SPSS Modeler or another application can be imported into the models palette For more information see the topic Model Types Supporting PMMI on p 198 gt Inthe models palette right click the palette and select Import PMML from the menu Figure 10 2 Impo
29. Scripting examples See the examples in the JBM SPSS Modeler Scripting and Automation Guide 6 Chapter 7 Demos Folder The data files and sample streams used with the application examples are installed in the Demos folder under the product installation directory This folder can also be accessed from the IBM SPSS Modeler 15 program group on the Windows Start menu or by clicking Demos on the list of recent directories in the File Open dialog box Figure 1 1 Selecting the Demos folder from the list of recently used directories Installation Directory VW File Name Files of Type open Insert cance Chapter New Features New and Changed Features in IBM SPSS Modeler 15 From this release onwards IBM SPSS Modeler has the following editions IBM SPSS Modeler Professional is the new name for the existing SPSS Modeler product IBM SPSS Modeler Premium is a separately licensed product that provides additional features to those supplied by SPSS Modeler Professional The new features for these editions are described in the following sections New features in IBM SPSS Modeler Professional The IBM SPSS Modeler Professional edition adds the following features in this release GLMM modeling node Generalized linear mixed models GLMMs extend the linear model so that the target is linearly related to the factors and covariates via a specified link function the target can have a non normal d
30. The MONTH TMG argument must be an integer in the range 1 to 12 datetime_now Timestamp Returns the current time as a timestamp datetime_second TIME Integer Returns the second from a TIME or timestamp The result is an integer in the range 0 to 59 datetime dan eter Returns the abbreviated name of the given DAY The we String argument must be an integer in the range 1 Sunday name DAY to 7 Saturday datetime_month_short_ Siri Returns the abbreviated name of the given MONTH name MONTH rng The argument must be an integer in the range 1 to 12 Returns the time value for the specified HOUR datetime_time HOUR MINUTE Time MINUTE and SECOND The arguments must be SECOND integers 149 CLEM Language Reference Function Result Description datetime_time ITEM Time Returns the time value of the given ITEM datetime_timestamp YEAR Returns the timestamp value for the given YEAR MONTH DAY HOUR MINUTE Timestamp MONTH DAY HOUR MINUTE and SECOND SECOND datetime_timestamp DATE Timestam Returns the timestamp value for the given DATE and TIME samp TIME Returns the timestamp value of the given number of datetime_timestamp NUMBER Timestamp seconds Returns the day of the week from the given DATE or datetime_weekday DATE Integer timestamp Returns the year from a DATE or timestamp The datetime_year DATE Integer result is an integer such as 2002 Returns th
31. This means that project items are saved both individually and as a reference in the project file cpj Because of this referential structure note the following m Project items must first be saved individually before being added to a project If an item is unsaved you will be prompted to save it before adding it to the current project Objects that are updated individually such as streams are also updated in the project file Manually moving or deleting objects such as streams nodes and output objects from the file system will render links in the project file invalid Creating a New Project New projects are easy to create in the IBM SPSS Modeler window You can either start building one if none is open or you can close an existing project and start from scratch 203 gt On the main menu click File gt Project gt New Project Adding to a Project gt gt Projects and Reports Once you have created or opened a project you can add objects such as data streams nodes and reports using several methods Adding Objects from the Managers Using the managers in the upper right corner of the IBM SPSS Modeler window you can add streams or output Select an object such as a table or a stream from one of the manager tabs Right click and click Add to Project If the object has been previously saved it will automatically be added to the appropriate objects folder in Classes view o
32. Using IBM SPSS Modeler with a Repository or File gt Projects gt Retrieve Project or File gt Outputs gt Retrieve Output gt Alternatively right click in the managers or project pane and click Retrieve on the pop up menu gt To retrieve a node on the SPSS Modeler main menu click Insert gt Node or SuperNode from Repository gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p 6 For specific port password and other connection details contact your local system administrator gt Inthe Repository Retrieve dialog box browse to the object select it and click the Retrieve button Choosing an Object to Retrieve Figure 9 12 Retrieving an object from the IBM SPSS Collaboration and Deployment Services Repository Repository Retrieve Search a overs sesten Repository rodev3 LongNodeName str Test 21881 str B MissingNodes str B Model Discriminant str B Model GeneralizedLinear str modelingintro str B newschancart_commented str cc_c51response str B newschancart_commented_2 str B exportcsy str B newschancart_commented_dj str File name basklinks str Fies of type Open as locked i O Keywords Version 1 2008 09 03 08 07 30 996 174 Chapter 9 Look in Shows the folder hierarchy for the current folder To navigate to a different folder select one from t
33. for example C Drug You can use this option to search for modeling nodes that generate a particular field Enter only one field name which must be an exact match ID equals Check this box and enter a node ID to search for a particular node with that identifier selecting this option disables all the preceding options Node IDs are assigned by the system when the node is created and can be used to reference the node for the purposes of scripting or automation Enter only one node ID which must be an exact match For more information see the topic Annotations on p 86 Search in SuperNodes This box is checked by default meaning that the search is performed on nodes both inside and outside SuperNodes Clear the box if you want to perform the search only on nodes outside SuperNodes at the top level of the stream Find When you have specified all the options you want click this button to start the search Nodes that match the specified options are listed in the lower part of the dialog box Select a node in the list to highlight it on the stream canvas Renaming Streams Using the Annotations tab in the stream properties dialog box you can add descriptive annotations for a stream and create a custom name for the stream These options are useful especially when generating reports for streams added to the project pane For more information see the topic Annotations on p 86 Stream
34. reports and anything else that you have created in IBM SPSS Modeler At first glance it may seem that SPSS Modeler projects are simply a way to organize output but they are actually capable of much more Using projects you can m Annotate each object in the project file m Use the CRISP DM methodology to guide your data mining efforts Projects also contain a CRISP DM Help system that provides details and real world examples on data mining with CRISP DM m Add non SPSS Modeler objects to the project such as a PowerPoint slide show used to present your data mining goals or white papers on the algorithms that you plan to use m Produce both comprehensive and simple update reports based on your annotations These reports can be generated in HTML for easy publishing on your organization s intranet Note If the project pane is not visible in the SPSS Modeler window click Project on the View menu Objects that you add to a project can be viewed in two ways Classes view and CRISP DM view Anything that you add to a project is added to both views and you can toggle between views to create the organization that works best Figure 11 1 CRISP DM view and Classes view of a project file Patient Records 8 fields 200 records Distribution of Drug i fal Generated Models ata Understanding Tables Graphs amp Reports fal Data Preparation Patient Records 6 fields 200 records E Modeling Distribution of Drug f Evalu
35. see the topic CLEM Reference Overview in Chapter 8 on p 127 Values and Data Types CLEM expressions are similar to formulas constructed from values field names operators and functions The simplest valid CLEM expression is a value or a field name Examples of valid values are 3 1 79 banana Examples of field names are Product_ID P NextField where Product is the name of a field from a market basket data set P NextField is the name of a parameter and the value of the expression is the value of the named field Typically field names start with a letter and may also contain digits and underscores _ You can use names that do not follow these rules if you place the name within quotation marks CLEM values can be any of the following m Strings for example c1 Type 2 a piece of free text m Integers for example 12 0 189 m Real numbers for example 12 34 0 0 0 0045 m Date time fields for example 05 12 2002 12 05 2002 12 05 02 It is also possible to use the following elements m Character codes for example a or 3 m Lists of items for example 1 2 3 Type 1 Type 2 Character codes and lists do not usually occur as field values Typically they are used as arguments of CLEM functions Quoting Rules Although the software is flexible when determining the fields values parameters and strings used in a CLEM expression the following general
36. A decision tree algorithm will build rules with only a single conclusion whereas association algorithms attempt to find many rules each of which may have a different conclusion Association nodes 4A The Apriori node extracts a set of rules from the data pulling out the rules with Ec the highest information content Apriori offers five different methods of selecting E E rules and uses a sophisticated indexing scheme to process large data sets efficiently For large problems Apriori is generally faster to train it has no arbitrary limit on the number of rules that can be retained and it can handle rules with up to 32 38 Chapter 4 preconditions Apriori requires that input and output fields all be categorical but delivers better performance because it is optimized for this type of data AON The CARMA model extracts a set of rules from the data without requiring you to aig specify input or target fields In contrast to Apriori the CARMA node offers build eee settings for rule support support for both antecedent and consequent rather than just antecedent support This means that the rules generated can be used for a wider variety of applications for example to find a list of products or services antecedents whose consequent is the item that you want to promote this holiday season The Sequence node discovers association rules in sequential or time oriented data A sequence is a list of item sets that tends to occur in a p
37. Aggregate node performance 234 allbutfirst function 141 allbutlast function 141 alphabefore function I4 and operator 137 annotating nodes 78 86 streams 78 86 annotations converting to comments 85 folder 207 project 206 application examples 4 applications applications of data mining BO arccos function I arccosh function 139 arcsin function 139 arcsinh function 139 arctan function 139 arctan2 function 139 arctanh function 139 attribute automation 105 backslash character in CLEM expressions backup stream files restoring 883 Binning node performance bitwise functions 140 BLANK function 102 134 156 blank handling CLEM functions 156 blanks 99 100 113 branches modeling and scoring 78 188 16 build rule node loading 90 cache enabling 50 216 231 flushing 52 57 options for nodes 50 231 Copyright IBM Corporation 1994 2012 saving setting up a cache 48 cache file node loading 90 canvas 18 case cdf_chisq function 139 cdf_f function 139 cdf_normal function 139 cdf_t function T39 Champion Challenger analysis 160 characters 127 128 charts saving output 89 checking CLEM expressions
38. Description Returns a randomly chosen element of LIST List items should be entered as ITEM1 ITEM2 ITEM_N Note that a list of field names can also be specified For more information see the topic Summarizing Multiple Fields in Chapter 7 on p 115 oneof LIST Any Returns a uniformly distributed random number of the same type INT or REAL starting from 1 to NUM If you use an integer then only integers are returned If you use a real decimal random NUM Number number then real numbers are returned decimal precision determined by the stream options The largest random number returned by the function could equal NUM This has the same properties as random NUM but starting from random0 NUM Number 0 The largest random number returned by the function will never equal X String Functions In CLEM you can perform the following operations with strings m Compare strings m Create strings m Access characters 142 Chapter 8 In CLEM a string is any sequence of characters between matching double quotation marks string quotes Characters CHAR can be any single alphanumeric character They are declared in CLEM expressions using single backquotes in the form of lt character gt such as 2 A or Z Characters that are out of bounds or negative indices to a string will result in undefined behavior Note Comparisons between strings that do and do not
39. Descriptions For each stream that you create IBM SPSS Modeler produces a stream description containing information on the contents of the stream This can be useful if you are trying to see what a stream does but you do not have SPSS Modeler installed for example when accessing a stream through IBM SPSS Collaboration and Deployment Services 75 Building Streams Figure 5 30 Opening section of stream description IBM SPSS Modeler Lasteavedby aos OOOO Contents Description amp Comment Scoring Information Modeling Information Description amp Comment Comment This stream predicts whether customers are likely to subscribe to our interactive news service based on characteristics of customers who have already subscribed This is the source data about our existing customers The stream description is displayed in the form of an HTML document consisting of a number of sections General Stream Information This section contains the stream name together with details of when the stream was created and last saved Description and Comments This section includes any m Stream annotations see Annotations on p 86 Comments not connected to specific nodes Comments connected to nodes in both the modeling and scoring branches of the stream Scoring Information This section contains information under various headings relating to the scoring branch of the stream Comments Includes
40. Due to minor differences in SQL implementation streams run in a database may return slightly different results from those returned when run in SPSS Modeler For similar reasons these differences may also vary depending on the database vendor Save As Default The options specified apply only to the current stream Click this button to set these options as the default for all streams 63 Building Streams Setting SQL logging and record status options for streams These settings include various options controlling the display of SQL statements generated by the stream and the display of the number of records processed by the stream Figure 5 20 Setting SQL logging and record status options for a stream Stream1 Select a setting With these settings you can control various aspects of SOL generation in the current stream Click Save As Default to Gi l anera use these settings as the default for all your streams Date Time Number formats 7 Logging E Display SQL in the messages log during stream execution Optimization Logging and status T Display SAL generation details in the messages log during stream preparation Display SQI Native ODBC A Reformat SQL for improved readabilit Status Show status for records O Never Every Display SOL in the messages log during stream execution Specifies whether SQL generated while running the stream is passed to the message
41. FIELD must be the name of a numeric field EXPR may be any expression MEAN FIELD EXPR Real evaluating to an integer greater than 0 If EXPR is omitted or if it exceeds the number of records received so far the average over all of the records received so far is returned Note that this function cannot be called from a script Returns the mean average of values for FIELD over the last EXPR records received by the current node including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 If EXPR is omitted or if it exceeds the number of records received so far the average over all of the records received so far is returned INT specifies the maximum number of values to look back This is far more efficient than using just two arguments Returns the first differential of FIELD1 The single argument form thus simply returns the DIFF1 FIELD Real difference between the current value and the previous value of the field Returns 0 if the relevant previous records do not exist MEAN FIELD EXPR INT Real The two argument form gives the first differential of DIFF1 FIELD1 FIELD2 Real FIELD with respect to FIELD2 Returns 0 if the relevant previous records do not exist Returns the second differential of FIELDI The single argument form thus simply returns the DIFF2 FIELD Real difference between the current value and the previous value of
42. For example say that you have set a cache midstream after a complex derive operation and that you have several graphs and reports attached downstream of this Derive node When running the stream the cache at the Derive node will be flushed and refilled but only for the first graph or report Subsequent terminal nodes will read data from the Derive node cache Display field and value labels in output Displays field and value labels in tables charts and other output If labels do not exist the field names and data values will be displayed instead Labels are turned off by default however you can toggle labels on an individual basis elsewhere in SPSS Modeler You can also choose to display labels on the output window using a toggle button available on the toolbar Figure 5 16 Toolbar icon used to toggle field and value labels Display execution times Displays individual execution times for stream nodes on the Execution Times tab after the stream is run For more information see the topic Viewing Node Execution imes on p 67 Save As Default The options specified apply only to the current stream Click this button to set these options as the default for all streams Setting date and time options for streams These options specify the format to use for various date and time expressions in the current stream 58 Chapter 5 Figure 5 17 Setting date and time options for a stream Select a setting Th
43. Handling Missing Values The functions can be used in conjunction with the FIELD function to identify the presence of blank or null values in one or more fields The fields can simply be flagged when blank or null values are present or they can be filled with replacement values or used in a variety of other operations You can count nulls across a list of fields as follows count_nulls cardtenure card2tenure card3tenure When using any of the functions that accept a list of fields as input the special functions FIELDS_BETWEEN and FIELDS_MATCHING can be used as shown in the following example count_nulls FIELDS_MATCHING card Figure 6 2 Using a Filler node to replace blank values with O in the selected field Filler Condition NULL FIELD ha Replace with ee Lox J cence Lape Bese You can use the undef function to fill fields with the system missing value displayed as null For example to replace any numeric value you could use a conditional statement such as if not Age gt 17 or not Age lt 66 then undef else Age endif This replaces anything that is not in the range with a system missing value displayed as null By using the not function you can catch all other numeric values including any negatives For more information see the topic Functions Handling Blanks and Null Values in Chapter 8 on p 156 104 Chapter 6 Not
44. IBM SPSS Modeler 02 000 cece ee teeta USING SHOMCUL KEYS ss53 4 che Ys eee A es ean Bee Saeed Vaated Dae eee PHINtIN Get evsisdis cance ote od Dens bark ohhh ean Wd bee Pat ace rman Gone ed Gone dae wach tune arn eee Automating IBM SPSS Modeler 0 0 a 4 Understanding Data Mining 29 Data Mining Vendo soacrei Pea ete ewe pelea s baud he ew Gear ee ke A Assessing the Data 0 0 ee een tent e ene n eee eens A Strategy for Data Mining 0 0 ccc nener aena aa aa n teen eens The CRISP DM Process Model 0 00 cece cece eee e nent n nena Types Of Models 1 ce eee een ent n en Die nee eas Data Mining Examples 0 00 een ene e een tent e ee nes 5 Building Streams 41 Stream Building Overview 0 0 ete n tee eens Building Data Streams 0 1 ete t nent nents Working with Nodes 0 cc ccc ccc eee te nee nee n eens Working with Str ams sep ess dacs ease eh oe Ota hata ha waleann se oad te aunain eae Stream DESCriptioNS asi ves eee ed ee ea eed Reh eae d oa Mee na ing em RUNNING StreaMS s4 iat5 asee 4s eee ee da the eda baw dae ie SA a Working with Models 1 0 0 ccc ccc cee eee nent n tenes Adding Comments and Annotations to Nodes and Streams 00 000 c ee een Saving Data Streams etiri raa EEA AE EEE REE EE E ete ents Loading FIGS arruont aa nae a n a Saw E EE elem goat Get Qi Mapping Data Streams 0 ccc tte ete ene teen eens TIPSAN Shortcuts sessce
45. Models Model browsers dialog box tabs with current focus tree viewers Annotations using the Annotations tab for output To print an object To print without previewing click the Print button on the toolbar To set up the page before printing select Page Setup from the File menu To preview before printing select Print Preview from the File menu To view the standard print dialog box with options for selecting printers and specifying appearance options select Print from the File menu Automating IBM SPSS Modeler Since advanced data mining can be a complex and sometimes lengthy process IBM SPSS Modeler includes several types of coding and automation support Control Language for Expression Manipulation CLEM is a language for analyzing and manipulating the data that flows along SPSS Modeler streams Data miners use CLEM extensively in stream operations to perform tasks as simple as deriving profit from cost and 28 Chapter 3 revenue data or as complex as transforming web log data into a set of fields and records with usable information For more information see the topic About in Chapter 7 on p 105 Scripting is a powerful tool for automating processes in the user interface Scripts can perform the same kinds of actions that users perform with a mouse or a keyboard You can set options for nodes and perform derivations using a subset of CLEM You can also specify output and manipulate generated models
46. Nodes bring data into SPSS Modeler m Record Ops Nodes perform operations on data records such as selecting merging and appending 19 IBM SPSS Modeler Overview m Field Ops Nodes perform operations on data fields such as filtering deriving new fields and determining the measurement level for given fields m Graphs Nodes graphically display data before and after modeling Graphs include plots histograms web nodes and evaluation charts m Modeling Nodes use the modeling algorithms available in SPSS Modeler such as neural nets decision trees clustering algorithms and data sequencing m Database Modeling Nodes use the modeling algorithms available in Microsoft SQL Server IBM DB2 and Oracle databases m Output Nodes produce a variety of output for data charts and model results that can be viewed in SPSS Modeler m Export Nodes produce a variety of output that can be viewed in external applications such as IBM SPSS Data Collection or Excel m SPSS Statistics Nodes import data from or export data to IBM SPSS Statistics as well as running SPSS Statistics procedures As you become more familiar with SPSS Modeler you can customize the palette contents for your own use For more information see the topic Customizing the Nodes Palette in Chapter 12 on p 223 Located below the Nodes Palette a report pane provides feedback on the progress of various operations such as when data is being read into the
47. PMML lt GeneralRegression gt models m As PMML lt Regression gt models For more information on PMML see the Data Mining Group website at www dmg org Setting User Information User Author Information Information you enter here can be displayed on the Annotations tab of nodes and other objects that you create 223 Customizing IBM SPSS Modeler Customizing the Nodes Palette Streams are built using nodes The Nodes Palette at the bottom of the IBM SPSS Modeler window contains all of the nodes it is possible to use in stream building For more information see the topic Nodes Palette in Chapter 3 on p 18 You can reorganize the Nodes Palette in two ways m Customize the Palette Manager For more information see the topic Customizing the Palette anager on p 223 m Change how palette tabs that contain subpalettes are displayed on the Nodes Palette For more information see the topic Creating a Subpalette on p 227 Figure 12 5 Record Ops tab on the Nodes Palette 000 0 000e Select Sample Balance Aggregate RFM Aggregate Sort Merge Append Distinct Customizing the Palette Manager The Palette Manager can be customized to accommodate your usage of IBM SPSS Modeler For example if you frequently analyze time series data from a database you might want to be sure that the Database source node the Time intervals node the Ti
48. SPSS Modeler Solution Publisher Runtime which enables you to execute the published streams IBM SPSS Modeler Server Adapters for IBM SPSS Collaboration and Deployment Services A number of adapters for IBM SPSS Collaboration and Deployment Services are available that enable SPSS Modeler and SPSS Modeler Server to interact with an IBM SPSS Collaboration and Deployment Services repository In this way an SPSS Modeler stream deployed to the repository 3 About IBM SPSS Modeler can be shared by multiple users or accessed from the thin client application IBM SPSS Modeler Advantage You install the adapter on the system that hosts the repository IBM SPSS Modeler Editions SPSS Modeler is available in the following editions SPSS Modeler Professional SPSS Modeler Professional provides all the tools you need to work with most types of structured data such as behaviors and interactions tracked in CRM systems demographics purchasing behavior and sales data SPSS Modeler Premium SPSS Modeler Premium is a separately licensed product that extends SPSS Modeler Professional to work with specialized data such as that used for entity analytics or social networking and with unstructured text data SPSS Modeler Premium comprises the following components IBM SPSS Modeler Entity Analytics adds a completely new dimension to IBM SPSS Modeler predictive analytics Whereas predictive analytics attempts to predict future behavior f
49. Select Table IBM SPSS Modeler Stream Canvas The stream canvas is the largest area of the IBM SPSS Modeler window and is where you will build and manipulate data streams Streams are created by drawing diagrams of data operations relevant to your business on the main canvas in the interface Each operation is represented by an icon or node and the nodes are linked together in a stream representing the flow of data through each operation You can work with multiple streams at one time in SPSS Modeler either in the same stream canvas or by opening a new stream canvas During a session streams are stored in the Streams manager at the upper right of the SPSS Modeler window Nodes Palette Most of the data and modeling tools in IBM SPSS Modeler reside in the Nodes Palette across the bottom of the window below the stream canvas For example the Record Ops palette tab contains nodes that you can use to perform operations on the data records such as selecting merging and appending To add nodes to the canvas double click icons from the Nodes Palette or drag and drop them onto the canvas You then connect them to create a stream representing the flow of data Figure 3 6 Record Ops tab on the nodes palette TIT Select Sample Balance Aggregate RFM Aggregate Sort Merge Append Distinct Each palette tab contains a collection of related nodes used for different phases of stream operations such as m Sources
50. The target field must be categorical Multiple splits into more than two subgroups are allowed The Decision List node identifies subgroups or segments that show a higher or lower likelihood of a given binary outcome relative to the overall population For example you might look for customers who are unlikely to churn or are most likely to respond favorably to a campaign You can incorporate your business knowledge into the model by adding your own custom segments and previewing alternative models side by side to compare the results Decision List models consist of a list of rules in which each rule has a condition and an outcome Rules are applied in order and the first rule that matches determines the outcome Linear regression models predict a continuous target based on linear relationships between the target and one or more predictors 36 Chapter 4 Zn i N 5 mis fy we Tar E a AN C2 e afl The PCA Factor node provides powerful data reduction techniques to reduce the complexity of your data Principal components analysis PCA finds linear combinations of the input fields that do the best job of capturing the variance in the entire set of fields where the components are orthogonal perpendicular to each other Factor analysis attempts to identify underlying factors that explain the pattern of correlations within a set of observed fields For both approaches the goal is to find a small number of d
51. This may seem obvious but be aware that although data might be available it may not be in a form that can be used easily IBM SPSS Modeler can import data from databases through ODBC or from files The data however might be held in some other form on a machine that cannot be directly accessed It will need to be downloaded or dumped in a suitable form before it can be used It might be scattered among different databases and sources and need to be pulled 31 Understanding Data Mining together It may not even be online If it exists only on paper data entry will be required before you can begin data mining Check whether the data covers the relevant attributes The object of data mining is to identify relevant attributes so including this check may seem odd at first It is very useful however to look at what data is available and to try to identify the likely relevant factors that are not recorded In trying to predict ice cream sales for example you may have a lot of information about retail outlets or sales history but you may not have weather and temperature information which is likely to play a significant role Missing attributes do not necessarily mean that data mining will not produce useful results but they can limit the accuracy of resulting predictions A quick way of assessing the situation is to perform a comprehensive audit of your data Before moving on consider attaching a Data Audit node to your data source an
52. You can lock an object to prevent other users from updating any of its existing versions or creating new versions A locked object is indicated by a padlock symbol over the object icon 178 Chapter 9 Figure 9 16 Locked object To lock an object In the repository explorer window right click the required object Click Lock To unlock an object In the repository explorer window right click the required object Click Unlock Deleting Repository Objects Before deleting an object from the repository you must decide if you want to delete all versions of the object or just a particular version To Delete All Versions of an Object In the repository explorer window right click the required object Click Delete Objects To Delete the Most Recent Version of an Object In the repository explorer window right click the required object Click Delete To Delete a Previous Version of an Object In the repository explorer window right click the required object Click Delete Versions Select the version s to delete and click OK 179 Using IBM SPSS Modeler with a Repository Figure 9 17 Select versions to delete a Repository Select Versions To Delete K Version Labels Size Creation Date Created By 1 2008 09 03 0 none 4 KB Wed Sep 03 14 admin Information for selected version Name basklinks str Version 0 2007 03 26 14 27 28 398 Labels none Created By admin Creation Date May 23 2007
53. a project gt Right click the root project folder and click Transfer Project gt If prompted log in to IBM SPSS Collaboration and Deployment Services Repository gt Specify the new location for the project and click OK Setting Project Properties You can customize a project s contents and documentation by using the project properties dialog box To access project properties gt Right click an object or folder in the project pane and click Project Properties gt Click the Project tab to specify basic project information Figure 11 5 Setting project properties Mortgage Retention Project Contents Save unsaved objects as files on the local file system objects in the Repository F Update object references when loading project Lot canoa Created Shows the project s creation date not editable 206 Chapter 11 Summary You can enter a summary for your data mining project that will be displayed in the project report Contents Lists the type and number of components referenced by the project file not editable Save unsaved object as Specifies whether unsaved objects should be saved to the local file system or stored in the repository For more information see the topic About the IBM SPSS Collaboration and Deployment Services Repository in Chapter 9 on p 158 Update object references when loading project Select this option to update the project s r
54. a replacement source node fixed dat Merge Step 4 Check mapped fields In the dialog box that opens check that the software is mapping fields properly from the replacement data source to the stream Any unmapped essential fields are displayed in red These fields are used in stream operations and must be replaced with a similar field in the new data source in order for downstream operations to function properly For more information see the topic Examining Mapped Fields on p 95 After using the dialog box to ensure that all essential fields are properly mapped the old data source is disconnected and the new data source is connected to the stream using a Filter node called Map This Filter node directs the actual mapping of fields in the stream An Unmap Filter node is also included on the stream canvas The Unmap Filter node can be used to reverse field name mapping by adding it to the stream It will undo the mapped fields but note that you will have to edit any downstream terminal nodes to reselect the fields and overlays Figure 5 46 New data source successfully mapped to the stream Transactions Filter NU gt gt Se Merge 94 Chapter 5 Mapping between Streams Similar to connecting nodes this method of data mapping does not require you to set essential fields beforehand With this method you simply connect from one stream to another using Map to from the Data Mapping pop up menu This type of data mapp
55. about our existing customers NewsChan sav This is where we generate the model from SE NEVWSCHAN and this contains the generated model NEWSCHAN The table indicates which of our existing customers accepted the news service M Table offer ve generate this node to use in the future with data about new customers to see I Table who is likely to accept the offer the table will show us who they are generated This stream predicts whether customers are likely to subscribe to our interactive news service based on characteristics of customers who have already subscribed Comment Colors M Custom colors Text The text of the comment Double click the text to change the field to an editable text box Links The name of the node to which the comment is attached If this field is empty the comment applies to the stream Positioning buttons These move a selected comment up or down in the list Comment Colors To change the foreground or background color of a comment select the comment select the Custom colors check box then select a color from the Background or Foreground list or both Click Apply then click the stream background to see the effect of the change Click OK to save the change Converting Annotations to Comments Annotations made to streams or SuperNodes can be converted into comments In the case of streams the annotation is converted to a freestanding comment that is it is not attached to any node
56. an object Repository Store Location intormaton Tons Security Permissions Owner Read Principal The repository username of the user or group who has access rights on this object Permissions The access rights that this user or group has for the object Add Enables you to add one or more users or groups to the list of those with access rights on this object For more information see the topic Adding a User to the Permissions List on p 169 Modify Enables you to modify the access rights of the selected user or group for this object Read access is granted by default This option enables you to grant additional access rights namely Owner Write Delete and Modify Permissions Delete Deletes the selected user or group from the permissions list for this object 169 Using IBM SPSS Modeler with a Repository Adding a User to the Permissions List Figure 9 10 Adding a user to the permissions list for an object Select User or Group z everyone admin dedre dimensions Select provider Choose a security provider for authentication The repository can be configured to use different security providers if necessary contact your local administrator for more information Find Enter the repository username of the user or group you want to add and click Search to display that name in the user list To add more than one username at a time leave this field blank an
57. and manage data mining projects groups of files related to a data mining task There are two ways to view projects you create in IBM SPSS Modeler in the Classes view and the CRISP DM view The CRISP DM tab provides a way to organize projects according to the Cross Industry Standard Process for Data Mining an industry proven nonproprietary methodology For both experienced and first time data miners using the CRISP DM tool will help you to better organize and communicate your efforts 21 IBM SPSS Modeler Overview Figure 3 10 CRISP DM view _ E fe unsaved project a Patient Records 8 fields 200 records Distribution of Drug Data Understanding Data Preparation Modeling Evaluation Deployment The Classes tab provides a way to organize your work in SPSS Modeler categorically by the types of objects you create This view is useful when taking inventory of data streams and models Figure 3 11 Classes view E unsaved project B Streams Generated Models Tables Graphs amp Reports Patient Records 8 fields 200 records Distribution of Drug i Other IBM SPSS Modeler Toolbar At the top of the IBM SPSS Modeler window you will find a toolbar of icons that provides a number of useful functions Following are the toolbar buttons and their functions Create new stream E Open stream O a Save stream Print current stream 22 Chapter 3 Cut amp move to
58. any effect Optimize syntax execution This method of stream rewriting increases the efficiency of operations that incorporate more than one node containing IBM SPSS Statistics syntax Optimization is achieved by combining the syntax commands into a single operation instead of running each as a separate operation Optimize other execution This method of stream rewriting increases the efficiency of operations that cannot be delegated to the database Optimization is achieved by reducing the amount of data in the stream as early as possible While maintaining data integrity the stream is rewritten to push operations closer to the data source thus reducing data downstream for costly operations such as joins Enable parallel processing When running on a computer with multiple processors this option allows the system to balance the load across those processors which may result in faster performance Use of multiple nodes or use of the following individual nodes may benefit from parallel processing C5 0 Merge by key Sort Bin rank and tile methods and Aggregate using one or more key fields Generate SOL Select this option to enable SQL generation allowing stream operations to be pushed back to the database by using SQL code to generate execution processes which may improve performance To further improve performance Optimize SQL generation can also be selected to maximize the number of operations pushed back to the database
59. been checked are displayed in red If errors are found a message indicating the cause is displayed Figure 7 11 Invalid CLEM expression Field Storage Age Integer is_real ITEM Boolean Sex String is_number ITEM Boolean BP String _ Boolean Cholesterol String dali X Nea Rea Expression Check Status K Real Drug String Na_to_K Unknown F Check expression before saving oc Cr cn Ge The following items are checked m Correct quoting of values and field names Correct usage of parameters and global variables Valid usage of operators Existence of referenced fields Existence and definition of referenced globals If you encounter errors in syntax try creating the expression using the lists and operator buttons rather than typing the expression manually This method automatically adds the proper quotes for fields and values Find and Replace The Find Replace dialog box is available in places where you edit script or expression text including the script editor CLEM expression builder or when defining a template in the Report node When editing text in any of these areas press Ctrl F to access the dialog box making sure cursor has focus in a text area If working in a Filler node for example you can access the dialog box from any of the text areas on the Settings tab or from the text field in the Expression Builder 124 Chapter 7 v v Vv V vy Vv Figure 7 12 Find Replace dialog box ed Fi
60. characters such as tabs or newline characters classes or ranges of characters such as a through d any digit or non digit and boundaries such as the beginning or end of a line The following types of expressions are supported Character Matches Characters Matches X The character x The backslash character On The character with octal value On 0 lt n lt 7 125 Building CLEM Expressions Characters Matches Onn The character with octal value Onn 0 lt n lt 7 Omnn The character with octal value Omnn 0 lt m lt 3 0 lt n lt 7 xhh The character with hexadecimal value Oxhh uhhhh The character with hexadecimal value Oxhhhh t The tab character u0009 n The newline line feed character u000A r The carriage return character u000D f The form feed character u000C a The alert bell character u0007 e The escape character u001B cx The control character corresponding to x Matching Character Classes Character classes Matches abc a b or c simple class Aabc Any character except a b or c subtraction a zA Z a through z or A through Z inclusive range a d m p a through d or m through p union Alternatively this could be specified as a dm p a z amp amp def a through z and d e or f intersection a z
61. color by double clicking the corresponding row in the Color column and selecting a color from the list To specify a custom color scroll to the bottom of the list and click the Color entry Changes made here do not affect previously created graphs Click Default Values to revert to the system default settings for this tab Setting PMML Export Options On the PMML tab you can control how IBM SPSS Modeler exports models to Predictive Model Markup Language PMML For more information see the topic Importing and Exporting Models as PMML in Chapter 10 on p 196 222 Chapter 12 Figure 12 4 User Options dialog box PMML tab User Options Export PMML O With extensions As standard PMML V4 0 Standard PMML Options Export Linear and Logistic Regression Models as PML lt GeneralRegression Models PMML lt Regression gt Models Export PMML Here you can configure variations of PMML that work best with your target application m Select With extensions to allow PMML extensions for special cases where there is no standard PMML equivalent Note that in most cases this will produce the same result as standard PMML m Select As standard PMML to export PMML that adheres as closely as possible to the PMML standard Standard PMML Options When the As standard PMML option is selected you can choose one of two valid ways to export linear and logistic regression models m As
62. comments linked only to nodes in the scoring branch 76 Chapter 5 m Inputs Lists the input fields together with their storage types for example string integer real and so on Outputs Lists the output fields including the additional fields generated by the modeling node together with their storage types m Parameters Lists any parameters relating to the scoring branch of the stream and which can be viewed or edited each time the model is scored These parameters are identified when you click the Scoring Parameters button on the Deployment tab of the stream properties dialog box m Model Node Shows the model name and type for example Neural Net C amp R Tree and so on This is the model nugget selected for the Model node field on the Deployment tab of the stream properties dialog box m Model Details Shows details of the model nugget identified under the previous heading Where possible predictor importance and evaluation charts for the model are included Modeling Information Contains information relating to the modeling branch of the stream Comments Lists any comments or annotations that are connected to nodes in the modeling branch m Inputs Lists the input fields together with their role in the modeling branch in the form of the field role value for example Input Target Split and so on m Parameters Lists any parameters relating to the modeling branch of the stream and which can be viewed o
63. data stream Also located below the Nodes Palette a status pane provides information on what the application is currently doing as well as indications of when user feedback is required IBM SPSS Modeler Managers At the top right of the window is the managers pane This has three tabs which are used to manage streams output and models You can use the Streams tab to open rename save and delete the streams created in a session Figure 3 7 Streams tab The Outputs tab contains a variety of files such as graphs and tables produced by stream operations in IBM SPSS Modeler You can display save rename and close the tables graphs and reports listed on this tab 20 Chapter 3 Figure 3 8 Outputs tab E Patient Records M Plot of Na v K ut Histogram of Na_to_K J Distribution of Drug le Distribution of name m Table 21 fields 10 records Distribution of name 1 Web of region x maincrop x claimt jul Histogram of diff E table 10 fields 300 records The Models tab is the most powerful of the manager tabs This tab contains all model nuggets which contain the models generated in SPSS Modeler for the current session These models can be browsed directly from the Models tab or added to the stream in the canvas Figure 3 9 Models tab containing model nuggets IBM SPSS Modeler Projects On the lower right side of the window is the project pane used to create
64. event occurred or a condition was true Use the function SINCE to do this for example SINCE Income gt Outgoings This function returns the offset of the last record where this condition was true that is the number of records before this one in which the condition was true If the condition has never been true SINCE returns INDEX 1 Sometimes you may want to refer to a value of the current record in the expression used by SINCE You can do this using the function THIS which specifies that a field name always applies to the current record To find the offset of the last record that had a Concentration field value more than twice that of the current record you could use SINCE Concentration gt 2 THIS Concentration In some cases the condition given to SINCE is true of the current record by definition for example SINCE ID THIS ID 152 Chapter 8 For this reason SINCE does not evaluate its condition for the current record Use a similar function SINCEO if you want to evaluate the condition for the current record as well as previous ones if the condition is true in the current record SINCEO returns 0 Note functions cannot be called from scripts Function Result Description Returns the mean average of values for the specified MEE Real FIELD or FIELDS Returns the mean average of values for FIELD over the last EXPR records received by the current node including the current record
65. linked nugget in the stream the refresh model is chosen as follows If a model nugget has been defined in the Deployment tab of the stream properties dialog box and is also in the stream then that nugget becomes the refresh model If no nugget has been defined in the Deployment tab or if one has been defined but is not on the scoring branch then the nugget closest to the terminal node becomes the refresh model To illustrate this suppose that you have the following stream 192 Chapter 9 Figure 9 29 Scoring branch with more than one model in the stream pm_customer_train1 s Type Select 2 response a ae rig z x B Enterprise View Type response responge Analysis ae pm_customer_train1 s Type Select response You right click the Analysis node and use its menu to set the scoring branch which is now highlighted Doing so also designates the model closest to the Analysis node as the refresh model as indicated by the highlighted refresh link Figure 9 30 Scoring branch highlighted with multiple models and refresh link pm_customer_train1 s Type Select at response a a Enterprise View Type response T pm_customer_train1 s Type Select response However you decide that you want to use the other model nugget in the stream as the refresh model so from its menu you set its model link to be used as the refresh link 193 Using IBM
66. locale This option is selected by default and set to English United States Deselect to specify another language from the list of available languages and locales Managing Memory In addition to the Maximum memory setting specified in the System Options dialog box there are several ways you can optimize memory usage m Set up a cache on any nonterminal node so that the data is read from the cache rather than retrieved from the data source when you run the data stream This will help decrease the memory load for large data sets For more information see the topic Caching Options for Nodes in Chapter 5 on p 50 m Adjust the Maximum members for nominal fields option in the stream properties dialog box This option specifies a maximum number of members for nominal fields after which the measurement level of the field becomes Typeless For more information see the topic Setting general options for streams in Chapter 5 on p 55 m Force IBM SPSS Modeler to free up memory by clicking in the lower right corner of the window where the memory that SPSS Modeler is using and the amount allocated are displayed xxMB xxMB Clicking this region turns it a darker shade after which memory allocation figures will drop Once the region returns to its regular color SPSS Modeler has freed up all the memory possible Setting Default Directories You can specify the default directory used for file browsers and output
67. machine learning artificial intelligence and statistics The methods available on the Modeling palette allow you to derive new information from your data and to develop predictive models Each method has certain strengths and is best suited for particular types of problems SPSS Modeler can be purchased as a standalone product or used as a client in combination with SPSS Modeler Server A number of additional options are also available as summarized in the following sections For more information see http www ibm com software analytics spss products modeler IBM SPSS Modeler Products The IBM SPSS Modeler family of products and associated software comprises the following IBM SPSS Modeler IBM SPSS Modeler Server IBM SPSS Modeler Administration Console IBM SPSS Modeler Batch IBM SPSS Modeler Solution Publisher IBM SPSS Modeler Server adapters for IBM SPSS Collaboration and Deployment Services IBM SPSS Modeler SPSS Modeler is a functionally complete version of the product that you install and run on your personal computer You can run SPSS Modeler in local mode as a standalone product or use it in distributed mode along with IBM SPSS Modeler Server for improved performance on large data sets With SPSS Modeler you can build accurate predictive models quickly and intuitively without programming Using the unique visual interface you can easily visualize the data mining process With the support of the advanc
68. menus such as Alt F to access the File menu or press the Tab key to scroll through dialog box controls However there are special issues related to each of the product s main windows and helpful hints for navigating dialog boxes This section will cover the highlights of keyboard accessibility from opening a stream to using node dialog boxes to working with output Additionally lists of keyboard shortcuts are provided for even more efficient navigation Shortcuts for Navigating the Main Window You do most of your data mining work in the main window of IBM SPSS Modeler The main area is called the stream canvas and is used to build and run data streams The bottom part of the window contains the node palettes which contain all available nodes The palettes are organized on tabs corresponding to the type of data mining operation for each group of nodes For example nodes used to bring data into SPSS Modeler are grouped on the Sources tab and nodes used to derive filter or type fields are grouped on the Field Ops tab short for Field Operations The right side of the window contains several tools for managing streams output and projects The top half on the right contains the managers and has three tabs that are used to manage streams output and generated models You can access these objects by selecting the tab and an object from the list The bottom half on the right contains the project pane which allows you to organize your work
69. on p 52 Maximum members for nominal fields Select to specify a maximum number of members for nominal set fields after which the data type of the field becomes Typeless This option is useful when working with large nominal fields Note When the measurement level of a field is set to Typeless its role is automatically set to None This means that the fields are not available for modeling Limit set size for Kohonen and K Means modeling Select to specify a maximum number of members for nominal fields used in Kohonen nets and K Means modeling The default set size is 20 after which the field is ignored and a warning is raised providing information on the field in question Note that for compatibility this option also applies to the old Neural Network node that was replaced in version 14 of I BM SPSS Modeler some legacy streams may still contain this node Refresh source nodes on execution Select to automatically refresh all source nodes when running the current stream This action is analogous to clicking the Refresh button on a source node except that this option automatically refreshes all source nodes except User Input nodes for the current stream Note Selecting this option flushes the caches of downstream nodes even if the data has not changed Flushing occurs only once per running of the stream though which means that you can still use downstream caches as temporary storage for a single running
70. option to generate and display the report in an output window Note that you have the option to export the report to various file types from the output window Output to file Select this option to generate and save the report as a file of the type specified in the File type list Filename Specify a filename for the generated report Files are saved by default to the SPSS Modeler bin directory Use the ellipsis button to specify a different location 212 Chapter 11 File type Available file types are m HTML document The report is saved as a single HTML file If your report contains graphs they are saved as PNG files and are referenced by the HTML file When publishing your report on the Internet make sure to upload both the HTML file and any images it references m Text document The report is saved as a single text file If your report contains graphs only the filename and path references are included in the report Microsoft Word document The report is saved as a single document with any graphs embedded directly into the document Microsoft Excel document The report is saved as a single spreadsheet with any graphs embedded directly into the spreadsheet Microsoft PowerPoint document Each phase is shown on a new slide Any graphs are embedded directly into the PowerPoint slides Output object When opened in SPSS Modeler this file cow is the same as the Output to screen option in the Report Format
71. or writing to an Oracle database be aware that unlike SPSS Modeler and unlike most other databases Oracle treats and stores empty string values as equivalent to null values This means that the same data extracted from an Oracle database may behave differently than when extracted from a file or another database and the data may return different results Handling Missing Values You should decide how to treat missing values in light of your business or domain knowledge To ease training time and increase accuracy you may want to remove blanks from your data set On the other hand the presence of blank values may lead to new business opportunities or additional insights In choosing the best technique you should consider the following aspects of your data m Size of the data set Number of fields containing blanks Amount of missing information 101 Handling Missing Values In general terms there are two approaches you can follow m You can exclude fields or records with missing values m You can impute replace or coerce missing values using a variety of methods Both of these approaches can be largely automated using the Data Audit node For example you can generate a Filter node that excludes fields with too many missing values to be useful in modeling and generate a Supernode that imputes missing values for any or all of the fields that remain This is where the real power of the audit comes in allowing you not only to
72. palette tabs supplied with SPSS Modeler except for the Favorites tab Changing the display order on the Nodes Palette After you have selected which palette tabs you want to display you can change the order in which they are displayed on the Nodes Palette gt Use the simple arrow buttons to move a palette tab up or down one row Moving them up moves them to the left of the Nodes Palette and vice versa gt Use the line arrow buttons to move a palette tab to the bottom or top of the list Those at the top of the list will be shown on the left of the Nodes Palette Displaying Subpalettes on a Palette Tab In the same way that you can control which palette tabs are displayed on the Nodes Palette you can control which subpalettes are available from their parent palette tab 227 Customizing IBM SPSS Modeler Figure 12 9 Subpalettes available for the Modeling Palette tab Sub Palettes Modeling Sub palettes can be created and edited here Sub palettes Sub Palette Name All Automated Classification Association Segmentation To select subpalettes for display on a palette tab From the Tools menu open the Palette Manager Select the palette that you require Click the Sub Palettes button the Sub Palettes dialog box is displayed v v vy Yy Using the check boxes in the Shown column select whether to include each subpalette on the palette tab The All subpalette is always shown and cannot be dele
73. results as income crop type White spaces within keywords are not trimmed however For example crop type with one space and crop type with two spaces are not the same The main text area can be used to enter lengthy annotations regarding the operations of the node or decisions made in the node For example when you are sharing and reusing streams it is helpful to take notes on decisions such as discarding a field with numerous blanks using a Filter node Annotating the node stores this information with the node You can also choose to include these annotations in a project report created from the project pane For more information see the topic Introduction to Projects in Chapter 11 on p 200 88 Chapter 5 Show annotation as comment For stream and SuperNode annotations only Check this box to convert the annotation to a freestanding comment that will be visible on the stream canvas For more information see the topic Adding Comments and Annotations to Nodes and Streams on p 78 ID Displays a unique ID that can be used to reference the node for the purpose of scripting or automation This value is automatically generated when the node is created and will not change Also note that to avoid confusion with the letter O zeros are not used in node IDs Use the copy button at the right to copy and paste the ID into scripts or elsewhere as needed Saving Data Streams v v v Yy
74. states loading 90 saving 88 Statistics files encoding 248 Statistics models B9 stop execution storing objects in the IBM SPSS Collaboration and Deployment Services Repository 164 stream 18 stream canvas settings 64 stream default encoding 56 stream descriptions 4 77 stream names 86 stream parameters 68 70 112 259 stream rewriting enabling 60 streams 12 adding comments 78 adding nodes 3 46 adding to projects 2021203 annotating 78 86 backup files 88 building 41 bypassing nodes 45 connecting nodes 43 deployment options 185 disabling nodes 46 loading 90 options 54 55 57 59 60 63464 renaming 74 86 running 77 saving 88 scaling to view 24 storing in the IBM SPSS Collaboration and Deployment Services Repository 170 viewing execution times 67 string functions 141 strings 27 29 manipulating in CLEM expressions 112 matching 112 replacing I12 stripchar function 41 strmember function 141 subpalette creation 227 displaying on palette tab 226 removing from palette tab 226 subscrs function 141 substring function 141 substring_between function
75. the field Returns 0 if the relevant previous records do not exist The two argument form gives the first differential of DIFF2 FIELD1 FIELD2 Real FIELD with respect to FIELD2 Returns 0 if the relevant previous records do not exist Returns the index of the current record Indices are allocated to records as they arrive at the current node The first record is given index 1 and the index is incremented by 1 for each subsequent record Returns the last value for FIELD that was not blank as defined in an upstream source or Type node If there are no nonblank values for FIELD in the records read so far null is returned Note that blank values also called user missing values can be defined separately for each field MAX FIELD Number Returns the maximum value for the specified FIELD INDEX Integer LAST_NON_BLANK FIELD Any 153 CLEM Language Reference Function Result Description Returns the maximum value for FIELD over the last EXPR records received so far including the current MAX FIELD EXPR Number record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 Returns the maximum value for FIELD over the last EXPR records received so far including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer MAX FIELD EXPR INT Number greater than 0 If EXP
76. the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 164 Stream Deployment Options The Deployment tab in the Stream Options dialog box allows you to specify options for deploying the stream You can deploy either as a stream or as a scenario When you deploy as a stream you can open and modify the stream in the thin client application IBM SPSS Modeler Advantage The stream is stored in the repository as a file with the extension str Deploying as a scenario stores the stream in the repository as a file with the extension scn Doing so also enables a stream to be used by Predictive Applications version 5 Whether you deploy as a stream or as a scenario you can take advantage of the additional functionality available with IBM SPSS Collaboration and Deployment Services such as multi user access automated scoring model refresh and Champion Challenger analysis From the Deployment tab you can also preview the stream description that IBM SPSS Modeler creates for the stream For more information see the topic Stream Descriptions in Chapter 5 on p 74 Note To ensure consistent access to enterprise data a stream that is deployed as a scenario must access its source data through IBM SPSS Collaboration and Deployment Services Enterprise View so in su
77. the original replicate COUNT STRING String string copied the specified number of times 145 CLEM Language Reference Function Result Description Enables you to remove specified characters from a string or field You can use this function for example to remove extra symbols such as currency notations from data to achieve a simple number or name For example using the syntax stripchar Cost returns a new field with the dollar sign removed from all values Note Be sure to use single backquotes to encapsulate the specified character stripchar CHAR STRING String Searches the string STRING for any character other than CHAR starting at the Mth character This function returns an integer substring indicating the point at which one is found or 0 if every character from the Nth onward is a CHAR If the function has an invalid offset for example an offset that is beyond the length of the string this function returns null locchar is often used in conjunction with the skipchar functions to determine the value of N the point at which to start searching the string For example skipchar s locchar s 1 MyString MyString skipchar CHAR N STRING Integer Similar to skipchar except that the search is skipchar_back CHAR N STRING Integer performed backward starting from the Nth character Extracts the first N characters from the specified string If th
78. the text box and press Enter m Right click the text box to display its menu and click Edit 83 Building Streams Edit the comment text You can use standard Windows shortcut keys when editing for example Ctrl C to copy text Other options during editing are listed in the pop up menu for the comment Click outside the text box once to display the resizing controls then again to complete the comment To resize a comment text box Select the comment to display the resizing controls Click and drag a control to resize the box Click outside the text box to save the change To move an existing comment If you want to move a comment but not its attached objects if any do one of the following Move the mouse pointer over the comment hold down the left mouse button and drag the comment to the new position m Select the comment hold down the Alt key and move the comment using the arrow keys If you want to move a comment together with any nodes or nuggets to which the comment is attached Select all the objects you want to move Do one of the following Move the mouse pointer over one of the objects hold down the left mouse button and drag the objects to the new position m Select one of the objects hold down the Alt key and move the objects using the arrow keys To disconnect a comment from a node or nugget Select one or more comments to be disconnected Do one of the following m Press F3 m Right cl
79. to print a stream For more information see the topic Changing the icon size for a stream in Chapter 3 on p R4 Copyright IBM Corporation 1994 2012 7 8 Chapter 2 Default settings for database connections You can now specify default settings for SQL Server and Oracle database connections as well as those already supported for IBM DB2 InfoSphere Warehouse Stream properties and optimization redesign The Options tab on the Stream Properties dialog box has been redesigned to group the options into categories The Optimization options have also moved from User Options to Stream Properties For more information see the topic Setting Options for Streams in Chapter 5 on p 54 Node execution timing You can now set an option to display individual execution times for the nodes in a stream For more information see the topic Viewing Node Execution Times in Chapter 5 on p 67 You can also set an option time_ecode_execution_log in the server configuration file to record these execution times in the message log Stream parameters in SOL queries from Database source node You can now include SPSS Modeler stream parameters in SQL queries that you enter in the Database source node Expression Builder supports in database functions If a stream connects to a database through a Database source node and you use the Expression Builder with a downstream node you can in
80. to upper case or lower case uppertolower CHAR m Removing specified characters such as ID_ or from a string variable stripchar CHAR STRING 113 Building CLEM Expressions Determining the length number of characters for a string variable length STRING Checking the alphabetical ordering of string values alphabefore STRING1 STRING2 Removing leading or trailing white space from values trim STRING trim_start STRING or trimend STRING m Extract the first or last n characters from a string startstring LENGTH STRING or endstring LENGTH STRING For example suppose you have a field named item that combines a product name with a four digit ID code ACME CAMERA D109 To create a new field that contains only the four digit code specify the following formula in a Derive node endstring 4 item m Matching a specific pattern STRING matches PATTERN For example to select persons with market anywhere in their job title you could specify the following in a Select node job_title matches market m Replacing all instances of a substring within a string replace SUBSTRING NEWSUBSTRING STRING For example to replace all instances of an unsupported character such as a vertical pipe with a semicolon prior to text mining use the replace function in a Filler node Under Fill in fields select all fields where the character may occur For the Replace condition select Always and specify the f
81. unit in the model nugget to identify the strong units This may give you a sense of the appropriate number of clusters The TwoStep node uses a two step clustering method The first step makes a single pass through the data to compress the raw input data into a manageable set of subclusters The second step uses a hierarchical clustering method to progressively merge the subclusters into larger and larger clusters TwoStep has the advantage of automatically estimating the optimal number of clusters for the training data It can handle mixed field types and large data sets efficiently P AN The Anomaly Detection node identifies unusual cases or outliers that do not conform E 7 to patterns of normal data With this node it is possible to identify outliers even if u they do not fit any previously known patterns and even if you are not exactly sure what you are looking for In Database Mining Models SPSS Modeler supports integration with data mining and modeling tools that are available from database vendors including Oracle Data Miner IBM DB2 InfoSphere Warehouse and Microsoft Analysis Services You can build score and store models inside the database all from within the SPSS Modeler application For full details see the SPSS Modeler In Database Mining Guide available on the product DVD IBM SPSS Statistics Models If you have a copy of IBM SPSS Statistics installed and licensed on your computer you can access and run
82. value too high will cause paging The running time of the neural network algorithms depends on the required level of accuracy You can control the running time by setting a stopping condition in the node s dialog box K Means The K Means clustering algorithm has the same options for controlling memory usage as the neural network algorithms Performance on data stored on disk is better however because access to the data is sequential Performance CLEM Expressions CLEM sequence functions functions that look back into the data stream must store enough of the data to satisfy the longest look back For operations whose degree of look back is unbounded all values of the field must be stored An unbounded operation is one where the 235 Performance Considerations for Streams and Nodes offset value is not a literal integer for example OFFSET Sales Month The offset value is the field name Month whose value is unknown until executed The server must save all values of the Sales field to ensure accurate results Where an upper bound is known you should provide it as an additional argument for example OFFSET Sales Month 12 This operation instructs the server to store no more than the 12 most recent values of Sales Sequence functions bounded or otherwise almost always inhibit SQL generation Appendix A Accessibility in IBM SPSS Modeler Overview of Accessibility in IBM SPSS Modeler This release offers gr
83. values are available in IBM SPSS Modeler such as m Calculating the sine of the specified angle sin NUM m Calculating the natural log of numeric fields log NUM m Calculating the sum of two numbers NUM1 NUM2 For more information see the topic Numeric Functions in Chapter 8 on p Working with Times and Dates 138 Time and date formats may vary depending on your data source and locale The formats of date and time are specific to each stream and are set in the stream properties dialog box The following examples are commonly used functions for working with date time fields 115 Building CLEM Expressions Calculating Time Passed You can easily calculate the time passed from a baseline date using a family of functions similar to the following one This function returns the time in months from the baseline date to the date represented by the date string DATE as a real number This is an approximate figure based on a month of 30 0 days date_in_months Date Comparing Date Time Values Values of date time fields can be compared across records using functions similar to the following one This function returns a value of true if the date string DATE represents a date prior to that represented by the date string DATE2 Otherwise this function returns a value of 0 date_before Date1 Date2 Calculating Differences You can also calculate the difference between two times and two dates using functi
84. you have a field named DATE that is stored as a string with values Jan 2003 Feb 2003 and so on you could convert it to date storage as follows to_date DATE For this conversion to work select the matching date format MON YYYY as the default date format for the stream For more information see the topic Setting general options for streams in Chapter 5 on p 55 For an example that converts string values to dates using a Filler node see the stream broadband_create_models str installed in the Demos folder under the streams subfolder Dates stored as numbers Note that DATE in the previous example is the name of a field while to_date is a CLEM function If you have dates stored as numbers you can convert them using the datetime_date function where the number is interpreted as a number of seconds since the base date or epoch datetime_date DATE By converting a date to a number of seconds and back you can perform calculations such as computing the current date plus or minus a fixed number of days for example datetime_date date_in_days DATE 7 60 60 24 Sequence Functions For some operations the sequence of events is important The application allows you to work with the following record sequences m Sequences and time series 151 CLEM Language Reference Sequence functions Record indexing Averaging summing and comparing values Monitoring change differentiation SINCE Of
85. 0 applications m Applications that can import and export files in PMML format For more information about using streams with IBM SPSS Modeler Advantage see Opening a Stream in IBM SPSS Modeler Advantage on p 195 To export a stream for use with Predictive Applications 5 0 follow the instructions for deploying as a scenario For more information see the topic Deploying Streams in Chapter 9 on p 184 For information on exporting and importing models as PMML files making it possible to share models with any other applications that support this format see Importing and Exporting Models as PMML on p 196 Note The Predictive Applications product has been superseded by IBM Analytical Decision Management Support for Predictive Applications will be withdrawn in a future release of SPSS Modeler Opening a Stream in IBM SPSS Modeler Advantage IBM SPSS Modeler streams can be used in conjunction with the thin client application I BM SPSS Modeler Advantage While it is possible to create customized applications entirely within IBM SPSS Modeler Advantage you can also use a stream already created in SPSS Modeler as the basis of an application workflow To open a stream in IBM SPSS Modeler Advantage gt Deploy the stream in the IBM SPSS Collaboration and Deployment Services repository being sure to click the Deploy as stream option For more information see the topic Deploying Streams in Chap
86. 12 10 2 djones ClearQuestRepor QJ BN_Drug gm Model 8 KB 0 2008 12 0 xyang Vi Fri Dec 05 06 4 user me 9 Cholest rol gm Model 8 KB 0 2008 12 2 none Mon Dec 29 08 Administrator DataCollection A Distribution_La Output 4 KB 2 2009 01 2 none Mon Jan 26 23 user X Drogue gm Model 8 KB 0 2008 12 2 none Mon Dec 29 08 Administrator Drug gm Model 9 KB 0 2008 09 0 none Wed Sep 03 12 djones Model 6 KB 0 2008 12 2 none Mon Dec 29 08 Administrator Dean DefectData DefectReportJobs DefectReports Derek Q Nuage nod Node 2 KB 0 2008 12 2 noeud Mon Dec 29 07 Administrator erel D operation xml Object 1 KB 0 2008 10 2 none Mon Oct 27 O7 admin Q source nod Node 1 KB 0 2008 12 2 none Fri Dec 26 10 4 Administrator a store_play cou Output 4 KB 0 2009 02 2 none Wed Feb 25 10 djones Stream scn Object 14 KB 1 2009 04 1 none Mon Apr 20 04 admin Stream2 str Stream 2 KB 0 2009 06 2 none Tue Jun 23 02 2 hyuan sunnior111111 Object 2 KB 1 2008 1 2 1 none Fri Dec 12 10 2 admin Table_Labels cou Output 20 KB 0 2008 12 0 example Fri Dec 05 06 5 user O test2 Object 2 KB 3 2009 03 0 none Thu Mar 05 22 1 admin test_b Object 0 2009 03 0 none Fri Mar 06 00 13 admin testsaveasopti Object 3 KB 1 2008 11 2 none Fri Nov 21 22 2 admin PES35DefectRep 0 WATERTREAT Model 90 KB 0 2008 12 2 none Mo
87. 12 2 none Mon Dec 29 07 Administrator PES40Planning PlanningData PlanningReports PMDemo E PMDemoDeta Information for selected version Name modelingintro str ii J Version 1 2009 05 28 04 21 15 478 PredictiveAppsRe Labels none QA Reports Created By admin E E QAinstall_Reports Creation Date May 28 2009 Keywords LabManagerRepa The explorer window initially displays a tree view of the folder hierarchy Click a folder name to display its contents Objects that match the current selection or search criteria are listed in the right pane with detailed information on the selected version displayed in the lower right pane The attributes displayed apply to the most recent version 164 Chapter 9 Storing Objects in the Repository Figure 9 5 Storing a model Add To Stream Browse Rename and Annotate Generate Modeling Node Save Model Save Model As Export PMML Add to Project X Delete You can store streams nodes models model palettes projects and output objects in the repository from where they can be accessed by other users and applications Note A separate license is required to access an IBM SPSS Collaboration and Deployment Services repository For more information see hitp www ibm com sojftware analytics spss products deployment cds You can also publish stream output to the repository in a format that enables other users to view it ove
88. 2007 11 1 none Mon Nov 12 20 AGVWWALTNEY Can_pe_deleted 2 KB 0 2008 12 1 none Fri Dec 12 10 2 djones ClearQuestRepor ty 8 KB 0 2008 12 0 xyang Vi Fri Dec 05 06 4 user cme 8 KB 0 2008 12 2 none Mon Dec 29 08 Administrator DataCollection EM 4 KB 2 2009 01 2 none Mon Jan 26 23 user Dean s 8 KB 0 2008 12 2 none Mon Dec 29 08 Administrator DefectData Drug gm 7 9 KB 0 2008 09 0 none _ Wed Sep 03 12 djones E DefectReportJobe j 6 KB 0 2008 12 2 none Mon Dec 29 08 Administrator Stream KB Defecthenoris 2 KB 0 2008 12 2 noeud Mon Dec 29 O7 Administrator 0 operation xml Object 1 KB 0 2008 10 2 none Mon Oct 27 O7 admin eJ source nod Node 1 KB 0 2008 12 2 none Fri Dec 26 10 4 Administrator store_play cou Output 4 KB 0 2009 02 2 none Wed Feb 25 10 djones Stream1 scn Object 14 KB 1 2009 04 1 none Mon Apr 20 04 admin I Stream2 str Stream 2 KB 0 2009 06 2 none Tue Jun 23 02 2 hyuan LJ sunnior111111 Object i 2 KB 1 2008 1 2 1 none Fri Dec 12 10 2 admin 9 Table_Labels cou Output 20 KB 0 2008 12 0 example Fri Dec 05 06 5 user Max test2 Object 2 KB 3 2009 03 0 none Thu Mar 05 22 1 admin D test_b Object 0 2009 03 0 none Fri Mar 06 00 13 admin PES3SDefectRep Wl C testsaveasopti Object 3KB1 2008 11 2 none Fri Nov 21 22 2 admin PES35Planning QJ WATERTREAT Model 90 KB 0 2008
89. 4 looks ahead four records in the sequence that is to records that have not yet passed through this node to obtain the value Note that a negative look ahead offset must be specified as a constant For positive offsets only OFFSET FIELD EXPR Any EXPR may also be an arbitrary CLEM expression which is evaluated for the current record to give the offset In this case the three argument version of this function should improve performance see next function If the expression returns anything other than a non negative integer this causes an error that is it is not legal to have calculated lookahead offsets Note A self referential OFFSET function cannot use literal lookahead For example in a Filler node you cannot replace the value of field1 using an expression such as OFFSET field1 2 154 Chapter 8 Function Result Description OFFSET FIELD EXPR INT Performs the same operation as the OFFSET function with the addition of a third argument JNT which specifies the maximum number of values to look back In cases where the offset is computed from an expression this third argument should improve performance For example in an expression such as OFFSET Foo Month 12 the system knows to keep only the last twelve values of Foo otherwise it has to store every value just in case In cases where the offset value is a constant including negative lookahead offsets which mu
90. 5 220 3694 157 72 468 78 380500 334714 268 6367 557 36 14 158000 145149106 1263 839 282 27 134000 138747 302 1892 730 From the Generate menu you can create several types of nodes Locking Nodes To prevent other users from amending the settings of one or more nodes in a stream you can encapsulate the node or nodes in a special type of node called a SuperNode and then lock the SuperNode by applying password protection Working with Streams Once you have connected source process and terminal nodes on the stream canvas you have created a stream As a collection of nodes streams can be saved annotated and added to projects You can also set numerous options for streams such as optimization date and time settings parameters and scripts These properties are discussed in the topics that follow In IBM SPSS Modeler you can use and modify more than one data stream in the same SPSS Modeler session The right side of the main window contains the managers pane which helps you to navigate the streams outputs and models that are currently open If you cannot see the managers pane click Managers on the View menu then click the Streams tab 54 Chapter 5 Figure 5 14 Streams tab in the managers pane with pop up menu options i Save Stream Ctr Save Stream As bfficemove w Store as Stream Deploy Add to Project El Stream Properties Close Stream A New Stream Ctri N Open St
91. 8 240 245246 example 243 244 scripting 27 105 finding and replacing text 123 scrolling setting options 64 SDEV function 152 SDEV function 150 152 sdev_n function 115 138 searching for nodes in a stream 73 searching COP for connections searching for objects in the IBM SPSS Collaboration and Deployment Services Repository 75 sequence functions 150 152 server adding connections I4 default directory 216 logging in searching COP for servers 14 session parameters 68 70 112 set command 68 12 sets 57 shortcuts general usage 96 keyboard 26 238 240 242 sign function 38 sin function 139 SINCE function 152 SINCE function 150 152 single sign on 14 single sign on IBM SPSS Collaboration and Deployment Services Repository 58 61 sinh function 139 skipchar function 41 skipchar_back function 41 Sort node performance 233 soundex function 146 soundex_difference function 146 source nodes 42 data mapping 92 refreshing 57 spaces removing from strings I12 41 special characters removing from strings I12 special functions 157 SPSS Modeler Server SQL generation 60 logging 63 previewing sqrt function 138 startstring function 141 startup dialog box 220
92. Collaboration and Deployment Services must be configured to use a single sign on provider m The user must be logged in to a host that is compatible with the provider 160 Chapter 9 For more information see the topic Connecting to the Repository on p 161 Storing and Deploying Repository Objects Streams created in IBM SPSS Modeler can be stored in the repository just as they are as files with the extension str In this way a single stream can be accessed by multiple users throughout the enterprise For more information see the topic Storing Objects in the Repository on p 164 It is also possible to deploy a stream in the repository A deployed stream is stored as a file with additional metadata A deployed stream can take full advantage of the enterprise level features of IBM SPSS Collaboration and Deployment Services such as automated scoring and model refresh For example a model can be automatically updated at regularly scheduled intervals as new data becomes available Alternatively a set of streams can be deployed for Champion Challenger analysis in which streams are compared to determine which one contains the most effective predictive model You can deploy a stream in one of two ways as a stream with the extension str or as a scenario with the extension scn Deployment as a stream enables the stream to be used by the thin client application IBM SPSS Modeler Advantage
93. DM Guide which can be accessed along with other documentation from the Documentation folder on the installation disk m The CRISP DM Help system available from the Start menu or by clicking CRISP DM Help on the Help menu in IBM SPSS Modeler Types of Models IBM SPSS Modeler offers a variety of modeling methods taken from machine learning artificial intelligence and statistics The methods available on the Modeling palette allow you to derive new information from your data and to develop predictive models Each method has certain strengths and is best suited for particular types of problems The SPSS Modeler Applications Guide provides examples for many of these methods along with a general introduction to the modeling process This guide is available as an online tutorial and also in PDF format For more information see the topic Application Examples in Chapter 1 on p 5 Modeling methods are divided into three categories m Classification m Association m Segmentation Classification Models Classification models use the values of one or more input fields to predict the value of one or more output or target fields Some examples of these techniques are decision trees C amp R Tree QUEST CHAID and C5 0 algorithms regression linear logistic generalized linear and Cox regression algorithms neural networks support vector machines and Bayesian networks Classification models helps organizations to p
94. INT2 0 but is more efficient 141 CLEM Language Reference Function Result Description Counts the number of 1 or O bits in the two s complement representation of INT If INT is non negative N is the number of bits If INT is negative it is the number of 0 bits Owing to the sign extension there are an infinite number of 0 bits in a non negative integer or 1 bits in a negative integer It is always the case that integer_bitcount INT integer_bitcount INT 1 Returns the bit position N of the least significant bit integer_leastbit INT Integer set in the integer INT N is the highest power of 2 by which INT divides exactly Returns the length in bits of INT as a two s complement integer That is N is the smallest integer such that INT lt 1 lt lt N if INT gt 0 INT gt 1 lt lt N if INT lt 0 If integer_length INT Integer INT is non negative then the representation of INT as an unsigned integer requires a field of at least N bits Alternatively a minimum of N bits is required to represent INT as a signed integer regardless of its sign integer_bitcount INT Integer Tests the bit at position N in the integer ZNT and returns testbit INT N Boolean the state of bit N as a Boolean value which is true for 1 and false for 0 Random Functions The following functions are used to randomly select items or randomly generate numbers Function Result
95. If a stream includes a modeling node that is one from the Modeling or Database Modeling tab of the nodes palette a model nugget is created when the stream is run A model nugget is a container for a model that is the set of rules formulas or equations that enables you to generate predictions against your source data and which lies at the heart of predictive analytics Figure 5 32 Model nugget Sey When you successfully run a modeling node a corresponding model nugget is placed on the stream canvas where it is represented by a gold diamond shaped icon hence the name nugget You can open the nugget and browse its contents to view details about the model To view the predictions you attach and run one or more terminal nodes the output from which presents the predictions in a readable form Figure 5 33 Modeling and scoring branches in a stream 0 gt E i modeling branch La NewsChan say T NEWSCHAN iaso scoring branch NEWSCHAN A typical modeling stream consists of two branches The modeling branch contains the modeling node together with the source and processing nodes that precede it The scoring branch is created when you run the modeling node and contains the model nugget and the terminal node or nodes that you use to view the predictions For more information see the JBM SPSS Modeler Modeling Nodes guide Adding Comments and Annotations to Nodes and Streams You may need to d
96. Information When you save a stream node project output file or model nugget you can encrypt it to prevent its unauthorized use To do this you select an extra option when saving and add a password to the item being saved This encryption can be set for any of the items that you save and adds extra security to them it is not the same as the SSL encryption used if you are passing files between IBM SPSS Modeler and IBM SPSS Modeler Server When you try to open an encrypted item you are prompted to enter the password After you enter the correct password the item is decrypted automatically and opens as usual To Encrypt an Item gt In the Save dialog box for the item to be encrypted click Options The Encryption Options dialog box opens Figure 5 42 Encryption options when saving a file Encryption Options Y Encrypt this file Warning If you lose or forget the password it cannot be recovered Enter password aheaee Re enter password for confirmation Y Mask password es te gt Select Encrypt this file gt Optionally for further security select Mask password This displays anything you enter as a series of dots gt Enter the password Warning If you forget the password the file or model cannot be opened gt If you selected Mask password re enter the password to confirm that you entered it correctly gt Click OK to return to the Save dialog box Note If you sav
97. Labels dialog box enables you to m Apply labels to the selected object m Remove labels from the selected object m Define a new label and apply it to the object To apply labels to the object gt Select one or more labels in the Available Labels list gt Click the right arrow button to move the selected labels to the Applied Labels list gt Click OK To remove labels from the object gt Select one or more labels in the Applied Labels list gt Click the left arrow button to move the selected labels to the Available Labels list gt Click OK 184 Chapter 9 To define a new label and apply it to the object gt Type the label name in the New Label field gt Click the right arrow button to move the new label to the Applied Labels list gt Click OK Deploying Streams To enable a stream to be used with the thin client application I BM SPSS Modeler Advantage it must be deployed as a stream str file in the repository Whether a stream is deployed as a stream str file or as a scenario scn file the object can take full advantage of the enterprise level features of I BM SPSS Collaboration and Deployment Services For more information see the topic Storing and Deploying Repository Objects on p 160 To deploy the current stream File menu method gt On the main menu click File gt Store gt Deploy gt Choose the deployment type and complete the rest of the dialog box as neces
98. Map to Generate User Input Node Specify Essential Fields gt Run From Here Data mapping is tightly integrated into stream building If you try to connect to a node that already has a connection you will be offered the option of replacing the connection or mapping to that node Mapping Data to a Template To replace the data source for a template stream with a new source node bringing your own data into IBM SPSS Modeler you should use the Select Replacement Node option from the Data Mapping pop up menu This option is available for all nodes except Merge Aggregate and all terminal nodes Using the data mapping tool to perform this action helps ensure that fields are matched properly between the existing stream operations and the new data source The following steps provide an overview of the data mapping process Step 1 Specify essential fields in the original source node In order for stream operations to run properly essential fields should be specified For more information see the topic Specifying ssential Fields on p 94 Step 2 Add new data source to the stream canvas Using one of the source nodes bring in the new replacement data 93 Building Streams Step 3 Replace the template source node Using the Data Mapping option on the pop up menu for the template source node click Select Replacement Node then select the source node for the replacement data Figure 5 45 Selecting
99. Model Markup Language PMML User or author information such as your name initials and e mail address This information may be displayed on the Annotations tab for nodes and for other objects that you create To set stream specific options such as decimal separators time and data formats optimization stream layout and stream scripts use the Stream Properties dialog box available from the File and Tools menus Setting Notification Options Using the Notifications tab of the User Options dialog box you can set various options regarding the occurrence and type of warnings and confirmation windows in IBM SPSS Modeler You can also specify the behavior of the Outputs and Models tabs in the managers pane when new output and models are generated 218 Chapter 12 Figure 12 2 User Options dialog box Notifications tab User Options Y Show stream execution feedback dialog Visual Notifications New Model M Add Model to Stream Y Close dialog upon completion IM Warn when a node overwrites a file IM Warn when a node overwrites a database table Sound Notifications E Mute all sounds Stream execution complete Error in stream execution Error in stream edit Stream added to Stream Viewer output added to Output Viewer Model added to Models Palette IM Replace previous model Select tab Always Or generated by current stream Never Flash tab If not selected Never Scro
100. NG Returns a value of true if CHAR is an uppercase letter character Otherwise this function returns a value of 0 For isuppercode CHAR Boolean example both isuppercode and isuppercode country_name 2 are valid expressions last CHAR String Returns the last character CHAR of STRING which must be at least one character long Returns the length of the string length STRING Integer STRING that is the number of characters in it 144 Chapter 8 Function Result Description Used to identify the location of characters in symbolic fields The function searches the string STRING for the character CHAR starting the search at the Nth character of STRING This function returns a value indicating the location starting at N where the character is found If the character is not found this function returns a value of 0 If locchar CHAR N STRING Integer the function has an invalid offset N for example an offset that is beyond the length of the string this function returns null For example locchar n 2 web_page searches the field called web_page for the n character beginning at the second character in the field value Note Be sure to use single backquotes to encapsulate the specified character Similar to locchar except that the search is performed backward starting from the Mth character For example locchar_back n 9 web_page searches the field web_page st
101. NewsChan sav Type N NEWSCHAN The text box is colored white to show that text can be entered When you have entered the text you click outside the text box The comment background changes to yellow to show that text entry is complete The comment remains selected allowing you to move resize or delete it 81 Building Streams Figure 5 37 Comment in edit mode NewsChan sayv Type Ma NEWSCHAN When you click again the border changes to solid lines to show that editing is complete Figure 5 38 Completed comment NewsChan sav Type ane NEWSCHAN Double clicking a comment changes the text box to edit mode the background changes to white and the comment text can be edited You can also attach comments to SuperNodes Operations Involving Comments You can perform a number of operations on comments You can Add a freestanding comment Attach a comment to a node or nugget Edit a comment Resize a comment Move a comment Disconnect a comment Delete a comment Show or hide all comments for a stream To add a freestanding comment gt Ensure that nothing is selected on the stream gt Do one of the following m On the main menu click Insert gt New Comment 82 Chapter 5 m Right click the stream background and click New Comment on the pop up menu m Click the New Comment button in the toolbar Enter the comment text or paste in text from the clipboard Click a node in t
102. PSS Collaboration and Deployment Services repository For more information see hittp www ibm com software analytics spss products deployment cds Figure 9 2 IBM SPSS Collaboration and Deployment Services Repository Login Repository Server Current Connection None Repository Port 8080 Set Credentials HEB g Ensure secure connection Repository The repository installation you want to access Generally this matches the name of the host server where the repository is installed You can connect to only one repository at a time Port The port used to host the connection typically 8080 by default Set Credentials Leave this box unchecked to enable the single sign on feature which attempts to log you in using your local computer username and password details If single sign on is not possible or if you check this box to disable single sign on for example to log in to an administrator account a further screen is displayed for you to enter your credentials 162 Chapter 9 Ensure secure connection Specifies whether a Secure Sockets Layer SSL connection should be used SSL is a commonly used protocol for securing data sent over a network To use this feature SSL must be enabled on the server hosting the repository If necessary contact your local administrator for details Entering Credentials for the Repository Figure 9 3 Entering IBM SPSS Collaboration and Deployment Ser
103. R is omitted or if it exceeds the number of records received so far the maximum value over all of the records received so far is returned INT specifies the maximum number of values to look back This is far more efficient than using just two arguments MIN FIELD Number Returns the minimum value for the specified FIELD Returns the minimum value for FIELD over the last EXPR records received so far including the current MIN FIELD EXPR Number record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 Returns the minimum value for FIELD over the last EXPR records received so far including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 If EXPR is omitted or if it exceeds the number of records received so far the minimum value over all of the records received so far is returned INT specifies the maximum number of values to look back This is far more efficient than using just two arguments MIN FIELD EXPR INT Number Returns the value of FIELD in the record offset from the current record by the value of EXPR A positive offset refers to a record that has already passed while a negative one specifies a lookahead to a record that has yet to arrive For example OFFSET Status 1 returns the value of the Status field in the previous record while OFFSET Status
104. SPSS Modeler you can specify a number of settings Display Options Screen readers tend to perform better when the visual contrast is greater on the screen If you already have a high contrast Windows setting you can choose to use these Windows settings for the software itself gt To set display options on the Tools menu click User Options gt Click the Display tab Use of Sounds for Notification By turning on or off sounds you can control the way you are alerted to particular operations in the software For example you can activate sounds for events such as node creation and deletion or the generation of new output or models gt To set notification options on the Tools menu click User Options gt Click the Notifications tab 238 Appendix A v v v iv Controlling the Automatic Launching of New Windows The Notifications tab on the User Options dialog box is also used to control whether newly generated output is launched in a separate window It may be easier for you to disable this option and open an output window as needed To set these options on the Tools menu click User Options Click the Notifications tab In the dialog box select New Output from the list in the Visual Notifications group Under Open Window select Never Keyboard Accessibility The product s functionality is accessible from the keyboard At the most basic level you can press Alt plus the appropriate key to activate window
105. SPSS Modeler Solution Publisher enables their delivery enterprise wide to decision makers or to a database About IBM Business Analytics IBM Business Analytics software delivers complete consistent and accurate information that decision makers trust to improve business performance A comprehensive portfolio of business intelligence predictive analytics financial performance and strategy management and analytic applications provides clear immediate and actionable insights into current performance and the ability to predict future outcomes Combined with rich industry solutions proven practices and professional services organizations of every size can drive the highest productivity confidently automate decisions and deliver better results As part of this portfolio IBM SPSS Predictive Analytics software helps organizations predict future events and proactively act upon that insight to drive better business outcomes Commercial government and academic customers worldwide rely on IBM SPSS technology as a competitive advantage in attracting retaining and growing customers while reducing fraud and mitigating risk By incorporating IBM SPSS software into their daily operations organizations become predictive enterprises able to direct and automate decisions to meet business goals and achieve measurable competitive advantage For further information or to reach a representative visit http www ibm c
106. SPSS Modeler with a Repository Figure 9 31 Scoring branch with refresh link switched to first model nugget e pm_customer_train1 s Type Select or ae 0 0 22 5 Enterprise View Type response response us kd pm_customer_train1 s Type Select response If you subsequently deselect both model links as refresh links only the scoring branch is highlighted not the links The deployment type is set to Scoring Only Figure 9 32 Scoring branch with multiple models and no refresh links pm_customer_train1 s Type Select ae response Enterprise View Type response response bm pm_customer_train1 s Type Select response Note You can choose to set one of the links to Replace status but not the other one In this case the model nugget chosen as the refresh model is the one that has a refresh link and which is closest to the terminal node when the scoring branch is designated 194 Chapter 9 No Models in Stream If there are no models in the stream or only models with no model links the deployment type is set to Scoring Only Checking a Scoring Branch for Errors When you designate the scoring branch it is checked for errors such as not having an Enterprise View node in the stream when deploying as a scenario Figure 9 33 Scoring branch with errors pm_customer_train1 s Type Select F response Pia ue
107. SS Modeler Social Network Analysis User Guide A guide to performing social network analysis with SPSS Modeler including group analysis and diffusion analysis m SPSS Modeler Text Analytics User s Guide Information on using text analytics with SPSS Modeler covering the text mining nodes interactive workbench templates and other resources m IBM SPSS Modeler Text Analytics Administration Console User Guide Information on installing and using the console user interface for monitoring and configuring IBM SPSS Modeler Server for use with SPSS Modeler Text Analytics The console is implemented as a plug in to the Deployment Manager application Application Examples While the data mining tools in SPSS Modeler can help solve a wide variety of business and organizational problems the application examples provide brief targeted introductions to specific modeling methods and techniques The data sets used here are much smaller than the enormous data stores managed by some data miners but the concepts and methods involved should be scalable to real world applications You can access the examples by clicking Application Examples on the Help menu in SPSS Modeler The data files and sample streams are installed in the Demos folder under the product installation directory For more information see the topic Demos Folder on p 6 Database modeling examples See the examples in the JBM SPSS Modeler In Database Mining Guide
108. STRING 1 STRING where N defaults to 1 isalphacode CHAR Boolean Returns a value of true if CHAR is a character in the specified string often a field name whose character code is a letter Otherwise this function returns a value of 0 For example isalphacode produce_num 1 isendstring SUBSTRING STRING Integer If the string STRING ends with the substring SUBSTRING then this function returns the integer subscript of SUBSTRING in STRING Otherwise this function returns a value of 0 islowercode CHAR Boolean Returns a value of true if CHAR is a lowercase letter character for the specified string often a field name Otherwise this function returns a value of 0 For example both islowercode and islowercode country_name 2 are valid expressions 143 CLEM Language Reference Function Result Description If SUBSTRING is a substring of STRING but does not start on the first character of STRING or end on the last then this function returns the subscript at which the substring starts Otherwise this function returns a value of 0 ismidstring SUBSTRING STRING Integer Returns a value of true if CHAR for the specified string often a field name is a isnumbercode CHAR Boolean character whose character code is a digit Otherwise this function returns a value of 0 For example isnumbercode product_id 2 If the string STRING starts with the substrin
109. Search on specific keywords In SPSS Modeler keywords are specified on the Annotation tab for a stream model or output object Description Search on specific terms in the description field In SPSS Modeler the description is specified on the Annotation tab for a stream model or output object Multiple search phrases can be separated by semicolons for example income crop type claim value Note that within a search phrase spaces matter For example crop type with one space and crop type with two spaces are not the same Modifying Repository Objects You can modify existing objects in the repository directly from SPSS Modeler You can m Create rename or delete folders m Lock or unlock objects m Delete objects Creating Renaming and Deleting Folders gt v v v Yy To perform operations on folders in the repository on the SPSS Modeler main menu click Tools gt Repository gt Explore Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p 16I For specific port password and other connection details contact your local system administrator Ensure that the Folders tab is active To create a new folder right click the parent folder and click New Folder To rename a folder right click it and click Rename Folder To delete a folder right click it and click Delete Folder Locking and Unlocking Repository Objects
110. To annotate a stream click Stream Properties on the Tools menu Alternatively you can right click a stream in the managers pane and click Stream Properties Click the Annotations tab 87 Building Streams Figure 5 40 Annotations tab options claimvalue v estincome X estincome Y claimvalue Tooltip text Maincrop as color overlay Used to explore the relationship between the value of claims and income as estimated by the model Crop type is used as an overlay to gain insight into whether there is a relationship between crop type and value of claims Created on September 16 2004 10 40 PM by jhealy ID B This object has not been saved ox J I run canca Ase geset Name Select Custom to adjust the autogenerated name or to create a unique name for the node as displayed on the stream canvas Tooltip text For nodes and model nuggets only Enter text used as a tooltip on the stream canvas This is particularly useful when working with a large number of similar nodes Keywords Specify keywords to be used in project reports and when searching for nodes in a stream or tracking objects stored in the repository see About the IBM SPSS Collaboration and Deployment Services Repository on p 158 Multiple keywords can be separated by semicolons for example income crop type claim value White spaces at the beginning and end of each keyword are trimmed for example income crop type will produce the same
111. Unlocking Repository Objects 0 0 c cece cece ete ees Deleting Repository Objects 0 nnna cect tet ete Managing Properties of Repository Objects 0 cc cect eee eens Viewing Folder Properties 0 0 0 ccc cee tte tenes Viewing and Editing Object Properties 20 0 ccc cece teens Managing Object Version Labels 0 cece cee ete vii Deploying Streams iia ei kiaia Laban Sie sabato heed ha aus A E adenine be 484 Stream Deployment Options nnna annsan aeaa 485 The Scoring Brant h ic srsucan iae wines esd a aE E a 4 eed etd owe Ka i 488 10 Exporting to External Applications 195 About Exporting to External Applications 0 0 0 0 ccc cece eee eens 495 Opening a Stream in IBM SPSS Modeler Advantage 0 cc cece ce eee eee 495 Importing and Exporting Models as PMML 0 0 0 ccc ce eee nes 496 Model Types Supporting PMML ooann anaa 498 11 Projects and Reports 200 Introduction to Projects nananana aanne nee ene e tent e eens 200 GRISP DM VIEW eiceta nee wae ian e dena dares dace added dated blanks 201 Glasses VIGW gt xs etstard a ata an acd ann ene aoe a a a athe ae a aa adh are ad 202 Building a ProjeCt ercis dence wh nate ca gia died ater a Glan Acca ot Aces Qed ee ais 202 Creating a New Project 0 eect etneet eee e eens 202 Adding to a Projeti ocsense aenea a at A be Dal a ENEE E EAE EENE etic Rady math Mande ambi ec 203 Transfe
112. When operations for a node have been pushed back to the database the node will be highlighted in purple when the stream is run m Database caching For streams that generate SQL to be executed in the database data can be cached midstream to a temporary table in the database rather than to the file system When combined with SQL optimization this may result in significant gains in performance For example the output from a stream that merges multiple tables to create a data mining view may be cached and reused as needed With database caching enabled simply right click any nonterminal node to cache data at that point and the cache is automatically created directly in the database the next time the stream is run This allows SQL to be generated for downstream nodes further improving performance Alternatively this option can be disabled if needed such as when policies or permissions preclude data being written to the database If database caching or SQL optimization is not enabled the cache will be written to the file system instead For more information see the topic Caching Options for Nodes on p 50 m Use relaxed conversion This option enables the conversion of data from either strings to numbers or numbers to strings if stored in a suitable format For example if the data is kept in the database as a string but actually contains a meaningful number the data can be converted for use when the pushback occurs Note
113. a zero of any kind This function is defined as log NUM log 10 negate NUM eee Used to negate NUM Returns the corresponding number with the opposite sign Used to round NUM to an integer by taking intof NUM 0 5 if round NUM Integer NUM is positive or intof NUM 0 5 if NUM is negative Used to determine the sign of NUM This operation returns sign NUM Number 1 0 or 1 if NUM is an integer If NUM is a real it returns g 1 0 0 0 or 1 0 depending on whether NUM is negative zero or positive sqrt NUM Real Returns the square root of NUM NUM must be positive Returns the sum of values from a list of numeric fields or null sum_n LIST Number if all of the field values are null For more information see the topic Summarizing Multiple Fields in Chapter 7 on p 15 139 CLEM Language Reference Function Result Description mean_n LIST Minbar Returns the mean value from a list of numeric fields or null if E all of the field values are null sdev_n LIST Nmber Returns the standard deviation from a list of numeric fields or null if all of the field values are null Trigonometric Functions All of the functions in this section either take an angle as an argument or return one as a result In both cases the units of the angle radians or degrees are controlled by the setting of the relevant stream option Function Re
114. able pass directly from the Derive node The Filter node is disconnected from the stream Figure 5 6 Bypassing a previously connected Filter node 2 Database Derive Filter e Table To Bypass a Node gt On the stream canvas use the middle mouse button to double click the node that you want to bypass Alternatively you can use Alt double click Note You can undo this action clicking Undo on the Edit menu or by pressing Ctrl Z 46 Chapter 5 Disabling Nodes in a Stream Process nodes with a single input within streams can be disabled with the result that the node is ignored during running of the stream This saves you from having to remove or bypass the node and means you can leave it connected to the remaining nodes You can still open and edit the node settings however any changes will not take effect until you enable the node again For example you might have a stream that filters several fields and then builds models with the reduced data set If you want to also build the same models without fields being filtered to see if they improve the model results you can disable the Filter node When you disable the Filter node the connections to the modeling nodes pass directly through from the Derive node to the Type node Figure 5 7 Disabled Filter node in a stream Drug DRUGIn Na_to_K Discard Fields Define A Drug To Disable a Node On the stream canvas right click th
115. about the object Repository Store N Location Topics Securty Version Label LATEST E All SLRM TrainingData E Baseline a O OE m oo O O Expiration None Date july 30 201 fai sore carea Crer Author The username of the user creating the object in the repository By default this shows the username used for the repository connection but you can change this name here Version Label Select a label from the list to indicate the object version or click Add to create a new label Avoid using the character in the label Ensure that no boxes are checked if you do not want to assign a label to this object version For more information see the topic Viewing and Editing Object Properties on p 180 Description A description of the object Users can search for objects by description see note Keywords One or more keywords that relate to the object and which can be used for search purposes see note Expiration A date after which the object is no longer visible to general users although it can still be seen by its owner and by the repository administrator To set an expiration date select the Date option and enter the date or choose one using the calendar button Store Stores the object at the current location Note Information in the Description and Keywords fields is treated as distinct from anything entered in SPSS Modeler on
116. ad the data from the data source d A Derive node which you use to add the new calculated field to the data set 2 gt A Select node which you use to set up selection criteria to exclude records from the data stream A Table node which you use to display the results of your manipulations onscreen Building Data Streams IBM SPSS Modeler s unique interface lets you mine your data visually by working with diagrams of data streams At the most basic level you can build a data stream using the following steps Add nodes to the stream canvas Connect the nodes to form a stream Specify any node or stream options Run the stream Copyright IBM Corporation 1994 2012 41 42 Chapter 5 Figure 5 1 Completed stream on the stream canvas Fie Edit Insert View Tools SuperNode Window Help Su G xe Bex hZ ree te 2S Olen H Var File Derive Select Table Business Under Data Understanding Data Preparation Modeling 00 00 A a AAE Database Var File Auto Data Prep Select Sample Aggregate Derive ype Filter Graphboard Auto Classifier Auto Numeric Auto Cluster Table Flat File Dat This section contains more detailed information on working with nodes to create more complex data streams It also discusses options and settings for nodes and streams For step by step examples of stream building using the data shipped with SPSS Modeler in the Demos folder of your pro
117. al If you are viewing this information softcopy the photographs and color illustrations may not appear Trademarks IBM the IBM logo ibm com and SPSS are trademarks of IBM Corporation registered in many jurisdictions worldwide A current list of IBM trademarks is available on the Web at http www ibm com legal copytrade shtml Intel Intel logo Intel Inside Intel Inside logo Intel Centrino Intel Centrino logo Celeron Intel Xeon Intel SpeedStep Itanium and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries Linux is a registered trademark of Linus Torvalds in the United States other countries or both Microsoft Windows Windows NT and the Windows logo are trademarks of Microsoft Corporation in the United States other countries or both UNIX is a registered trademark of The Open Group in the United States and other countries Java and all Java based trademarks and logos are trademarks of Sun Microsystems Inc in the United States other countries or both Other product and service names might be trademarks of IBM or other companies 251 Notices lar Java 508 compliance 236 abs function 138 accessibility 236 247 example 244 features in IBM SPSS Modeler 236 tips in IBM SPSS Modeler 246 adding to a project 202 adding IBM SPSS Modeler Server connections 14
118. amily of functions for handling fields with datetime storage of string variables representing dates and times The formats of date and time used are specific to each stream and are specified in the stream properties dialog box The date and time functions parse date and time strings according to the currently selected format When you specify a year in a date that uses only two digits that is the century is not specified IBM SPSS Modeler uses the default century that is specified in the stream properties dialog box 147 CLEM Language Reference Note Date and time functions cannot be called from scripts Function Result Description TODAY String If you select Rollover days mins in the stream properties dialog box this function returns the current date as a string in the current date format If you use a two digit date format and do not select Rollover days mins this function returns null on the current server Note that this function cannot be called from a script to_time ITEM Time Converts the storage of the specified field to a time to_date ITEM Date Converts the storage of the specified field to a date to_timestamp ITEM Timestamp Converts the storage of the specified field to a timestamp to_datetime ITEM Datetime Converts the storage of the specified field to a date time or timestamp value datetime_date ITEM Date Returns the date value for a
119. amp amp bc a through z except for b and c subtraction Alternatively this could be specified as ad z a z amp amp m p a through z and not m through p subtraction Alternatively this could be specified as a lq z Predefined Character Classes Predefined character classes Matches Any character may or may not match line terminators d Any digit 0 9 D A non digit 40 9 s A white space character t n xOB f r S A non white space character s w A word character a zA Z_0 9 W A non word character w Boundary Matches Boundary matchers Matches A The beginning of a line The end of a line b A word boundary B A non word boundary A The beginning of the input 126 Chapter 7 Boundary matchers Matches Z The end of the input but for the final terminator if any z The end of the input Chapter CLEM Language Reference CLEM Reference Overview This section describes the Control Language for Expression Manipulation CLEM which is a powerful tool used to analyze and manipulate the data used in IBM SPSS Modeler streams You can use CLEM within nodes to perform tasks ranging from evaluating conditions or deriving values to inserting data into reports For more information see the topic About CLEM in Chapter 7 on p 105 A subset of the CLEM l
120. anguage can also be used when you are scripting in the user interface This allows you to perform many of the same data manipulations in an automated fashion CLEM expressions consist of values field names operators and functions Using the correct syntax you can create a wide variety of powerful data operations For more information see the topic CLEM Examples in Chapter 7 on p 08 CLEM Datatypes CLEM datatypes can be made up of any of the following Integers Reals Characters Strings Lists Fields Date Time Rules for Quoting Although IBM SPSS Modeler is flexible when you are determining the fields values parameters and strings used in a CLEM expression the following general rules provide a list of good practices to use in creating expressions m Strings Always use double quotes when writing strings such as Type 2 Single quotes can be used instead but at the risk of confusion with quoted fields m Fields Use single quotes only where necessary to enclose spaces or other special characters such as Order Number Fields that are quoted but undefined in the data set will be misread as strings Parameters Always use single quotes when using parameters such as P threshold Characters Always use single backquotes gt such as stripchar d drugA Copyright IBM Corporation 1994 2012 127 128 Chapter 8 For more
121. argument INT specifies the maximum number of records to look back If EXPR has never been true INT is INDEX 1 SINCEO EXPR Considers the current record while SINCE does not SINCEO returns 0 if EXPR is true for the current record SINCEO EXPR INT Adding the second argument INT specifies the maximum number of records to look back SUM FIELD Returns the sum of values for the specified FIELD or FIELDS 155 CLEM Language Reference Function Result Description Returns the sum of values for FIELD over the last EXPR records received by the current node including the current record FIELD must be the name of a numeric field EXPR may be any expression SUMIFIELD EXPR Number evaluating to an integer seis than O If EXPR is omitted or if it exceeds the number of records received so far the sum over all of the records received so far is returned Returns the sum of values for FIELD over the last EXPR records received by the current node including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 SUMIFIELD EXPR INT Number If EXPR is omitted if it seo number of records received so far the sum over all of the records received so far is returned INT specifies the maximum number of values to look back This is far more efficient than using just two arguments Returns the value of t
122. arting from the ninth character and moving backward toward the start of the string If the function has an invalid offset for locchar_back CHAR N STRING Integer example an offset that is beyond the length of the string this function returns null Ideally you should use locchar_back in conjunction with the function length lt field gt to dynamically use the length of the current value of the field For example locchar_back n length web_page web_page Input can be either a string or character which is used in this function to return a new item of the same type with any lowertoupper CHAR CHAR or lowercase characters converted to their lowertoupper STRING String uppercase equivalents For example lowertoupper a lowertoupper My string and lowertoupper field_name 2 are all valid expressions Returns true if a string matches a specified pattern The pattern must be a string literal it cannot be a field name containing a pattern A question mark can be included in the pattern to match exactly one character an asterisk matches zero or more characters To match a literal question mark or asterisk rather than using these as wildcards a backslash can be used as an escape character matches Boolean Within the specified STRING replace String all instances of SUBSTRING with NEWSUBSTRING replace SUBSTRING NEWSUBSTRING STRING Returns a string that consists of
123. as the default for all streams Setting optimization options for streams You can use the Optimization settings to optimize stream performance Note that the performance and optimization settings on IBM SPSS Modeler Server if used override any equivalent settings in the client Note Database modeling and SQL optimization require that SPSS Modeler Server connectivity be enabled on the IBM SPSS Modeler computer With this setting enabled you can access database algorithms push back SQL directly from SPSS Modeler and access SPSS Modeler Server To verify the current license status choose the following from the SPSS Modeler menu Help gt About gt Additional Details If connectivity is enabled you see the option Server Enablement in the License Status tab For more information see the topic Connecting to IBM SPSS Modeler Server in Chapter 3 on p 13 61 Building Streams Figure 5 19 Setting stream optimization options OStream1 Select a setting Use these settings to optimize performance of the current stream Note that optimization settings if used on SPSS ere Modeler Server override those on the client Click Save As Default to use these settings as the default for all your streams Date Time Number formats Y Enable stream rewriting Optimization IM Optimize SOL generation Logging and Status IM Optimize syntax execution Fi Optimize other execution Layout F
124. assess the current state of your data but to take action based on the assessment Handling Records with Missing Values If the majority of missing values is concentrated in a small number of records you can just exclude those records For example a bank usually keeps detailed and complete records on its loan customers If however the bank is less restrictive in approving loans for its own staff members data gathered for staff loans is likely to have several blank fields In such a case there are two options for handling these missing values m You can use a Select node to remove the staff records m If the data set is large you can discard all records with blanks Handling Fields with Missing Values If the majority of missing values is concentrated in a small number of fields you can address them at the field level rather than at the record level This approach also allows you to experiment with the relative importance of particular fields before deciding on an approach for handling missing values If a field is unimportant in modeling it probably is not worth keeping regardless of how many missing values it has For example a market research company may collect data from a general questionnaire containing 50 questions Two of the questions address age and political persuasion information that many people are reluctant to give In this case Age and Political_persuasion have many missing values Field Measurement Level In det
125. ate does not exist Returns the time in months from the date or timestamp represented by DATE to that represented by DATE2 date_months_difference Real ber This i fi based DATE1 DATE2 ea as a real number This is an approximate figure base i on a month of 30 4375 days If DATE2 is before DATE this function returns a negative number datetime_date YEAR MONTH Dat Creates a date value for the given YEAR MONTH and DAY ES DAY The arguments must be integers Returns the day of the month from a given DATE or datetime_day DATE Integer timestamp The result is an integer in the range 1 to 31 Returns the full name of the given DAY The argument datetime_day_name DAY String must be an integer in the range 1 Sunday to 7 Saturday Returns the hour from a TIME or timestamp The datetime_hour TIME Integer result is an integer in the range 0 to 23 datetime_in_seconds TIME Real Returns the seconds portion stored in TIME datetime_in_seconds DATE Returns the accumulated number converted into datetime_in_seconds DATE Real seconds from the difference between the current DATE TIME or DATETIME and the baseline date 1900 01 01 datetime_minute TIME Integer Returns the minute from a TIME or timestamp The result is an integer in the range 0 to 59 datetime_month DATE Integer Returns the month from a DATE or timestamp The result is an integer in the range 1 to 12 datetime_month_name Stri Returns the full name of the given MONTH
126. ation see the topic Comparison Functions in Chapter 8 on p 135 Referencing Multiple Response Sets The special MULTI_RESPONSE_SET function can be used to reference all of the fields in a multiple response set For example if the three car fields in the previous example are included in a multiple response set named car_rankings the following would return the same result max_index MULTI_RESPONSE_SET car_rankings The Expression Builder You can type CLEM expressions manually or use the Expression Builder which displays a complete list of CLEM functions and operators as well as data fields from the current stream allowing you to quickly build expressions without memorizing the exact names of fields or 118 Chapter 7 functions In addition the Builder controls automatically add the proper quotes for fields and values making it easier to create syntactically correct expressions Figure 7 5 Expression Builder dialog box PowerFlux T and OFFSET PowerFlux 1l T Boolean Integer Boolean Temperature Integer Boolean Y Pressure Integer Boolean Uptime Integer Boolean Status Integer Boolean 7 _ Outcome Integer Boolean y Pressure Warnings Unknown Integer p Tempinc Unknown is_integer ITEM Returns a value of true if ITEM type is an integer Otherwise returns a value of false Check expression before saving ox cansei Note The Expression Builder is not supported
127. ation i Other in fl Deployment Copyright IBM Corporation 1994 2012 200 201 Projects and Reports CRISP DM View By supporting the Cross Industry Standard Process for Data Mining CRISP DM IBM SPSS Modeler projects provide an industry proven and non proprietary way of organizing the pieces of your data mining efforts CRISP DM uses six phases to describe the process from start gathering business requirements to finish deploying your results Even though some phases do not typically involve work in SPSS Modeler the project pane includes all six phases so that you have a central location for storing and tracking all materials associated with the project For example the Business Understanding phase typically involves gathering requirements and meeting with colleagues to determine goals rather than working with data in SPSS Modeler The project pane allows you to store your notes from such meetings in the Business Understanding folder for future reference and inclusion in reports Figure 11 2 CRISP DM view B Patient Records 8 fields 200 records I Distribution of Drug B Data Understanding ata Preparation B Modeling EE Evaluation i Deployment The CRISP DM view in the project pane is also equipped with its own Help system to guide you through the data mining life cycle From SPSS Modeler this help can be accessed by clicking CRISP DM Help on the Help menu Note If the project pane is not visible
128. ation on how to use the power of your database to improve performance and extend the range of analytical capabilities through third party algorithms IBM SPSS Modeler Server Administration and Performance Guide Information on how to configure and administer IBM SPSS Modeler Server 5 About IBM SPSS Modeler m IBM SPSS Modeler Administration Console User Guide Information on installing and using the console user interface for monitoring and configuring SPSS Modeler Server The console is implemented as a plug in to the Deployment Manager application m IBM SPSS Modeler Solution Publisher Guide SPSS Modeler Solution Publisher is an add on component that enables organizations to publish streams for use outside of the standard SPSS Modeler environment m IBM SPSS Modeler CRISP DM Guide Step by step guide to using the CRISP DM methodology for data mining with SPSS Modeler m IBM SPSS Modeler Batch User s Guide Complete guide to using IBM SPSS Modeler in batch mode including details of batch mode execution and command line arguments This guide is available in PDF format only SPSS Modeler Premium Documentation The SPSS Modeler Premium documentation suite excluding installation instructions is as follows m IBM SPSS Modeler Entity Analytics User Guide Information on using entity analytics with SPSS Modeler covering repository installation and configuration entity analytics nodes and administrative tasks m IBM SP
129. ay of the year for example 2000032 represents the 32nd day of 2000 or 1 February 2000 DAY Day of the week in the current locale for example Monday Tuesday in English MONTH Month in the current locale for example January February DD MM YY 15 01 63 130 Chapter 8 Format Examples DD MM YYYY 15 01 1963 MM DD YY 01 15 63 MM DD YYYY 01 15 1963 DD MM YY 15 01 63 DD MM YYYY 15 01 1963 MM DD YY 01 15 63 MM DD YYYY 01 15 1963 DD MM YY 15 01 63 DD MM YYYY 15 01 1963 MM DD YY 01 15 63 MM DD YYYY 01 15 1963 DD MON YY 15 JAN 63 15 jan 63 15 Jan 63 DD MON YY 15 JAN 63 15 jan 63 15 Jan 63 DD MON YY 15 JAN 63 15 jan 63 15 Jan 63 DD MON YYYY 15 JAN 1963 15 jan 1963 15 Jan 1963 DD MON YYYY 15 JAN 1963 15 jan 1963 15 Jan 1963 DD MON YYYY 15 JAN 1963 15 jan 1963 15 Jan 1963 MON YYYY Jan 2004 q Q YYYY Date represented as a digit 1 4 representing the quarter followed by the letter Q and a four digit year for example 25 December 2004 would be represented as 4 Q 2004 ww WK YYYY Two digit number representing the week of the year followed by the letters WK and then a four digit year The week of the year is calculated assuming that the first day of the week is Monday and there is at least one day in the first week Time The CLEM language supports the following time formats
130. ble that you have access to experts who know the data They can guide you in the identification of relevant attributes and can help to interpret the results of data mining distinguishing the true nuggets of information from fool s gold or artifacts caused by anomalies in the data sets 32 Chapter 4 A Strategy for Data Mining As with most business endeavors data mining is much more effective if done in a planned systematic way Even with cutting edge data mining tools such as IBM SPSS Modeler the majority of the work in data mining requires a knowledgeable business analyst to keep the process on track To guide your planning answer the following questions m What substantive problem do you want to solve m What data sources are available and what parts of the data are relevant to the current problem m What kind of preprocessing and data cleaning do you need to do before you start mining the data What data mining technique s will you use How will you evaluate the results of the data mining analysis How will you get the most out of the information you obtained from data mining The typical data mining process can become complicated very quickly There is a lot to keep track of complex business problems multiple data sources varying data quality across data sources an array of data mining techniques different ways of measuring data mining success and so on To stay on track it helps to have an explicit
131. by means of an options file The application provides a console user interface to monitor and configure your SPSS Modeler Server installations and is available free of charge to current SPSS Modeler Server customers The application can be installed only on Windows computers however it can administer a server installed on any supported platform IBM SPSS Modeler Batch While data mining is usually an interactive process it is also possible to run SPSS Modeler from a command line without the need for the graphical user interface For example you might have long running or repetitive tasks that you want to perform with no user intervention SPSS Modeler Batch is a special version of the product that provides support for the complete analytical capabilities of SPSS Modeler without access to the regular user interface An SPSS Modeler Server license is required to use SPSS Modeler Batch IBM SPSS Modeler Solution Publisher SPSS Modeler Solution Publisher is a tool that enables you to create a packaged version of an SPSS Modeler stream that can be run by an external runtime engine or embedded in an external application In this way you can publish and deploy complete SPSS Modeler streams for use in environments that do not have SPSS Modeler installed SPSS Modeler Solution Publisher is distributed as part of the IBM SPSS Collaboration and Deployment Services Scoring service for which a separate license is required With this license you receive
132. by selecting Set Directory or Set Server Directory from the File menu m Set Directory You can use this option to set the working directory The default working directory is based on the installation path of your version of I BM SPSS Modeler or from the command line path used to launch SPSS Modeler In local mode the working directory 217 Customizing IBM SPSS Modeler is the path used for all client side operations and output files if they are referenced with relative paths Set Server Directory The Set Server Directory option on the File menu is enabled whenever there is a remote server connection Use this option to specify the default directory for all server files and data files specified for input or output The default server directory is CLEO data where CLEO is the directory in which the Server version of SPSS Modeler is installed Using the command line you can also override this default by using the server_directory flag with the modelerclient command line argument Setting User Options You can set general options for IBM SPSS Modeler by selecting User Options from the Tools gt Options menu These options apply to all streams used in SPSS Modeler The following types of options can be set by clicking the corresponding tab Notification options such as model overwriting and error messages Display options such as graph and background colors PMML export options used when exporting models to Predictive
133. c Summarizing Multiple Fields in Chapter 7 on p 15 min ITEM1 ITEM2 Any Returns the lesser of the two items ITEM 1 or ITEM2 Returns the index of the field containing the minimum value from a list of numeric fields or 0 if all values are null For example if the third field listed contains the min_index LIST Integer minimum the index value 3 is returned If multiple fields contain the minimum value the one listed first leftmost is returned For more information see the topic Working with Multiple Response Data in Chapter 7 on p L17 Returns the minimum value from a list of numeric fields or min_n LIST Number null if all of the field values are null time_before TIME1 Bool Used to check the ordering of time values Returns a true TIME2 Corean value if TIME is before TIME2 Returns the value of each listed field at offset INT or NULL if the offset is outside the range of valid values that is less than 1 or greater than the number of listed fields All storage types supported value_at INT LIST Logical Functions CLEM expressions can be used to perform logical operations Function Result Description This operation is a logical conjunction and returns a true value if both COND and COND2 are true If COND is false then COND2 is not evaluated this makes it possible to have conjunctions where CONDI first tests that an operation in COND2
134. cates how the data values are stored in the parameter For example when working with values containing leading zeros that you want to preserve such as 008 you should select String as the storage type Otherwise the zeros will be stripped from the value Available storage types are string integer real time date and timestamp For date parameters note that values must be specified using ISO standard notation as shown in the next paragraph Value Lists the current value for each parameter Adjust the parameter as required Note that for date parameters values must be specified in ISO standard notation that is YYYY MM DD Dates specified in other formats are not accepted Type optional If you plan to deploy the stream to an external application select a measurement level from the list Otherwise it is advisable to leave the Type column as is If you want to specify value constraints for the parameter such as upper and lower bounds for a numeric range select Specify from the list 70 Chapter 5 Note that long name storage and type options can be set for parameters through the user interface only These options cannot be set using scripts Click the arrows at the right to move the selected parameter further up or down the list of available parameters Use the delete button marked with an X to remove the selected parameter Specifying Runtime Prompts for Parameter Values If you have streams where you might need to ent
135. cee ee eee eee eee e eee e eee e een n nnn n enn 6 2 New Features A New and Changed Features in IBM SPSS Modeler 15 00 0 0 cece cece eee nee A New features in IBM SPSS Modeler Professional 0000 0 cece eee eaeee A New features in IBM SPSS Modeler Premium 0 0 0 c cece cece eens 40 New Nodes in This Release annann 40 3 IBM SPSS Modeler Overview 12 Getting Started wc se ssc orenat anak einda ADRE os eae w Lee wad Fee eee eens 42 Starting IBM SPSS Modeler 00 0 0 ccc eet eee eee eens 42 Launching from the Command Line 00 cc cece eee ee eee ees 43 Connecting to IBM SPSS Modeler Server 2 0 0 cc cece eee eee ees 43 Changing the Temp Directory 0 cece cect tenet eens 46 Starting Multiple IBM SPSS Modeler Sessions 0 00 cece cece teens dy IBM SPSS Modeler Interface ata Glance 0 0 ccc teens H IBM SPSS Modeler Stream Canvas 0 00 0 ccc eee ae 48 Nodes Palette 2 satan che a a a a Bae Dns datew da ait aes a a EE 48 IBM SPSS Modeler Managers 0 0 0 0 ccc een ence teen eens 49 IBM SPSS Modeler Projects 0 cece ce tee teen eee peA 20 IBM SPSS Modeler Toolbar ona naaaana naa eee eens 24 Customizing the Toolbar 0 20 0 te ee teen ees 23 Customizing the IBM SPSS Modeler Window 00 0 cece cee ee ees 23 Copyright IBM Corporation 1994 2012 iv Changing the icon size fora stream n on cette eens Using the Mouse in
136. certain SPSS Statistics routines from within SPSS Modeler to build and score models Further Information Detailed documentation on the modeling algorithms is also available For more information see the SPSS Modeler Algorithms Guide available on the product DVD 40 Chapter 4 Data Mining Examples The best way to learn about data mining in practice is to start with an example A number of application examples are available in the JBM SPSS Modeler Applications Guide which provides brief targeted introductions to specific modeling methods and techniques For more information see the topic Application Examples in Chapter 1 on p 5 Chapter Building Streams Stream Building Overview Data mining using IBM SPSS Modeler focuses on the process of running data through a series of nodes referred to as a stream This series of nodes represents operations to be performed on the data while links between the nodes indicate the direction of data flow Typically you use a data stream to read data into SPSS Modeler run it through a series of manipulations and then send it to a destination such as a table or a viewer For example suppose that you want to open a data source add a new field select records based on values in the new field and then display the results in a table In this case your data stream would consist of four nodes an iaip A Variable File node which you set up to re
137. ch a case the stream must include at least one Enterprise View source node within each designated scoring or modeling branch as applicable 186 Chapter 9 Figure 9 24 Stream Deployment options O modelingintro_deployment i n X Deployment type Model Refresh enables creation of streams and scenarios supporting scoring building and refresh features rDeployment Settings SF Scoring node Table Select any terminal node Modeling node 2 Creditrating Select a modeling node Model nugget P Credit rating Select a model nugget in the scoring branch Deploy as stream Deploy as scenario Deployment type Choose how you want to deploy the stream All streams require a designated scoring node before they can be deployed additional requirements and options depend on the deployment type m lt none gt The stream will not be deployed to the repository All options are disabled except stream description preview Scoring Only The stream is deployed to the repository when you click the Store button Data can be scored using the node that you designate in the Scoring node field m Model Refresh Same as for Scoring Only but in addition the model can be updated in the repository using the objects that you designate in the Modeling node and Model nugget fields Note Automatic model refresh is not supported by default in IBM SPSS Collaboration and Deployment Services so you must cho
138. cific fields as appropriate and then generate a SuperNode that imputes values using a number of methods This is the most flexible method and it also allows you to specify handling for large numbers of fields in a single node The following methods are available for imputing missing values Fixed Substitutes a fixed value either the field mean midpoint of the range or a constant that you specify Random Substitutes a random value based on a normal or uniform distribution Expression Allows you to specify a custom expression For example you could replace values with a global variable created by the Set Globals node Algorithm Substitutes a value predicted by a model based on the C amp RT algorithm For each field imputed using this method there will be a separate C amp RT model along with a Filler node that replaces blanks and nulls with the value predicted by the model A Filter node is then used to remove the prediction fields generated by the model Alternatively to coerce values for specific fields you can use a Type node to ensure that the field types cover only legal values and then set the Check column to Coerce for the fields whose blank values need replacing CLEM Functions for Missing Values There are several functions used to handle missing values The following functions are often used in Select and Filler nodes to discard or fill missing values m count_nulls LIST BLANK FIELD NULL FIELD undef 103
139. clipboard Paste selection im ix Redo Edit stream properties K Run current stream Stop stream Active only while stream is running Zoom in SuperNodes only No markup in stream Hide stream markup if any wiik OY Open stream in IBM SPSS Modeler Advantage a SY elke kwy OBS LE j Copy to clipboard Undo last action Search for nodes Preview SQL generation Run stream selection Add SuperNode Zoom out SuperNodes only Insert comment Show hidden stream markup Stream markup consists of stream comments model links and scoring branch indications For more information on stream comments see and Streams on p 78 Adding Comments and Annotations to Nodes For more information on scoring branch indications see The Scoring Branch on p 188 Model links are described in the JBM SPSS Modeling Nodes guide 23 IBM SPSS Modeler Overview Customizing the Toolbar gt gt You can change various aspects of the toolbar such as m Whether it is displayed m Whether the icons have tooltips available m Whether it uses large or small icons To turn the toolbar display on and off On the main menu click View gt Toolbar gt Display To change the tooltip or icon size settings On the main menu click View gt Toolbar gt Customize Click Show ToolTips or Large Buttons as required Customizing the IBM SPSS Modele
140. clude in database functions from the connected database directly in the expression you are building For more information see the topic Selecting Functions in Chapter 7 on p 120 IBM Cognos BI node enhancements The Cognos BI source node now supports importing Cognos list reports as well as data and additionally supports the use of parameters and filters For the Cognos BI source and export nodes SPSS Modeler now automatically detects the version of IBM Cognos BI in use Enhancements to Aggregate node The Aggregate node now supports several new aggregation modes for aggregate fields median count variance and first and third quartiles Merge node supports conditional merge You can now perform input record merges that depend on satisfying a condition You can specify the condition directly in the node or build the condition using the Expression Builder Enhancements to in database mining nodes for IBM DB2 InfoSphere Warehouse For in database mining with IBM DB2 InfoSphere Warehouse the ISW Clustering node now supports the Enhanced BIRCH algorithm in addition to demographic and Kohonen clustering In addition the ISW Association node provides a choice of layout for non transactional tabular data Table compression for database export When exporting to a database you can now specify table compression options for SQL Server and Oracle database connections as well as those already supported for IBM DB2 InfoSp
141. converting 150 manipulating 150 datetime functions datetime_date 146 datetime_day 146 datetime_day_name 146 datetime_day_short_name 146 datetime_hour 146 datetime_in_seconds 146 datetime_minute 146 datetime_month 146 datetime_month_name 1146 datetime_month_short_name 146 datetime_now datetime_second 146 datetime_time 146 datetime_timestamp 146 datetime_weekday 146 datetime_year 146 datetime_date function 135 decimal places display formats BY decimal symbol number display formats 56 decision trees accessibility 246 default project phase 201 degrees measurements units 60 deploying scenarios 185 deployment 160 deployment options scenarios 185 deployment type 185 dictionary file DIFF function 152 DIFF function 150 152 directory default 216 disable nodes 46 48 display formats currency 59 decimal places 59 grouping symbol 59 numbers 59 scientific 59 Distinct node performance 234 distribution functions 139 254 Index div function 138 documentation 4 domain name Windows IBM SPSS Modeler Server 13 DTD 197
142. cos function 139 cosh function 139 count_equal function L15 135 count_greater_than function 115 135 count_less_than function 15 1135 count_non_nulls function 1135 count_not_equal function 115 135 count_nulls function 102 15 135 count_substring function 41 CRISP DM 20 200 projects view 20 CRISP DM process model B2 currency display format 59 custom palette creation 225 subpalette creation 227 cut 21 J o9 data preview 52 data audit node use in exploration 29 Data Audit node use in data mining B1 data mapping tool 91 02 data mining 29 application examples A0 strategy B2 data streams building 41 data types 10 in parameters 70 database functions 120 date formats 58 294130 date functions 129 130 date_before 135 1146 date_days_difference 146 date_in_days 146 date_in_months 146 date_in_weeks 146 Index date_in_years 146 date_months_difference 146 date_weeks_difference 146 date_years_difference 146 TODAY function 146 date_before function 135 date time values 114 dates
143. create models which can accurately predict the correct drug for a patient given a set of test results The available patient data is age and sex The available test results are blood pressure blood cholesterol levels and blood ton counts for sodium Na and potassium K Five drugs are available A B C X and Y Y is the most popular choice Data Understanding The data understanding involves collecting data in order to become familiar with the data identify data quality problems and identify initial insights or interesting subsets Data Preparation This phase covers all activities involved in constructing the final datasets to be used in the modeling phase Modeling Tn this phase various modeling techniques are selected and applied and their Eee ee m Chapter 12 Customizing IBM SPSS Modeler Customizing IBM SPSS Modeler Options There are a number of operations you can perform to customize IBM SPSS Modeler to your needs Primarily this customization consists of setting specific user options such as memory allocation default directories and use of sound and color You can also customize the Nodes palette located at the bottom of the SPSS Modeler window Setting IBM SPSS Modeler Options There are several ways to customize and set options for IBM SPSS Modeler m Set system options such as memory usage and locale by clicking System Options on the Tools gt Options menu m Set user option
144. d By default IBM SPSS Modeler uses the system temporary directory to create temp files You can alter the location of the temporary directory using the following steps gt Create a new directory called spss and subdirectory called servertemp 17 IBM SPSS Modeler Overview gt Edit options cfg located in the config directory of your SPSS Modeler installation directory Edit the temp_directory parameter in this file to read temp_directory C spss servertemp gt After doing this you must restart the SPSS Modeler Server service You can do this by clicking the Services tab on your Windows Control Panel Just stop the service and then start it to activate the changes you made Restarting the machine will also restart the service All temp files will now be written to this new directory Note The most common error when you are attempting to do this is to use the wrong type of slashes Because of SPSS Modeler s UNIX history forward slashes are used Starting Multiple IBM SPSS Modeler Sessions If you need to launch more than one IBM SPSS Modeler session at a time you must make some changes to your IBM SPSS Modeler and Windows settings For example you may need to do this if you have two separate server licenses and want to run two streams against two different servers from the same client machine To enable multiple SPSS Modeler sessions gt Click Start gt All Programs gt IBM SPSS Modeler15 gt O
145. d into memory up to the limit and sorted using a fast hybrid quick sort algorithm If all the data fits in memory then the sort is complete Otherwise a merge sort algorithm is applied The sorted data is written to file and the next chunk of data is read into memory sorted and written to disk This is repeated until all the data has been read then the sorted chunks are merged Merging may require repeated passes over the data stored on disk At peak usage the Sort node will have two complete copies of the data set on disk sorted and unsorted The overall running time of the algorithm is on the order of N log N where N is the number of records Sorting in memory is faster than merging from disk so the actual running time can be reduced by allocating more memory to the sort The algorithm allocates to itself a fraction of physical RAM controlled by the IBM SPSS Modeler Server configuration option Memory usage multiplier To increase the memory used for sorting provide more physical RAM or increase this value Note that when the proportion of memory used exceeds the working set of the process so that part of the memory is paged to disk performance degrades because the memory access pattern of the in memory sort algorithm is random and can cause excessive paging The sort algorithm is used by several nodes other than the Sort node but the same performance rules apply Binning The Binning node reads the entire input data set to compute the bin b
146. d just click Search to display a list of all the repository usernames User list Select one or more usernames from the list and click OK to add them to the permissions list Modifying Access Rights for an Object Figure 9 11 Modifying access rights for an object Security Modify Permissions owner Read IM Write IM Delete T Modify Permissions ic wen ne Owner Select this option to give this user or group owner access rights to the object The owner has full control over the object including Delete and Modify access rights 170 Chapter 9 Read By default a user or group that is not the object owner has only Read access rights to the object Select the appropriate check boxes to add Write Delete and Modify Permissions access rights for this user or group Storing Streams You can store a stream as a str file in the repository from where it can be accessed by other users Note For information on deploying a stream to take advantage of additional repository features see Deploying Streams on p 184 To store the current stream gt On the main menu click File gt Store gt Store as Stream gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator gt Inthe Re
147. d running it to generate a full report Beware of noisy data Data often contains errors or may contain subjective and therefore variable judgments These phenomena are collectively referred to as noise Sometimes noise in data is normal There may well be underlying rules but they may not hold for 100 of the cases Typically the more noise there is in data the more difficult it is to get accurate results However SPSS Modeler s machine learning methods are able to handle noisy data and have been used successfully on data sets containing almost 50 noise Ensure that there is sufficient data In data mining it is not necessarily the size of a data set that is important The representativeness of the data set is far more significant together with its coverage of possible outcomes and combinations of variables Typically the more attributes that are considered the more records that will be needed to give representative coverage If the data is representative and there are general underlying rules it may well be that a data sample of a few thousand or even a few hundred records will give equally good results as a million and you will get the results more quickly Seek out the experts on the data In many cases you will be working on your own data and will therefore be highly familiar with its content and meaning However if you are working on data for another department of your organization or for a client it is highly desira
148. date it is returned unchanged Comparison Functions Comparison functions are used to compare field values to each other or to a specified string For example you can check strings for equality using An example of string equality verification is Class class 1 For purposes of numeric comparison greater means closer to positive infinity and lesser means closer to negative infinity That is all negative numbers are less than any positive number Function Result Description Returns the number of values from a list of fields that are equal to JTEM or null if TEM is null For more information see the topic Summarizing Multiple Fields in Chapter 7 on p 15 count_equal ITEM1 LIST Integer 136 Chapter 8 Function Result Description count_greater_than ITEM1 Int Returns the number of values from a list of fields that are LIST ee greater than TEM or null if JTEM is null count_less_than ITEM1 Int Returns the number of values from a list of fields that are LIST MERET less than ITEM or null if ITEM is null count_not_equal ITEM1 Int Returns the number of values from a list of fields that are LIST NIERET not equal to TEM or null if ITEM is null count_nulls LIST Integer Returns the number of null values from a list of fields count_non_nulls LIST Integer Return
149. de this setting applies to empty strings as well m Blank or user defined missing values These are values such as unknown 99 or 1 that are explicitly defined in a source node or Type node as missing Optionally you can also choose to treat nulls and white space as blanks which allows them to be flagged for special treatment and to be excluded from most calculations For example you can use the BLANK function to treat these values along with other types of missing values as blanks Copyright IBM Corporation 1994 2012 99 100 Chapter 6 Figure 6 1 Specifying missing values for a continuous variable age Values Measurement Continuous gt storage integer Values O Read from data Pass Specify values and labels 18 Lower Upper 67 E Extend values from data Check values Define blanks Missing values M Null IM White space E ent he Reading in mixed data Note that when you are reading in fields with numeric storage either integer real time timestamp or date any non numeric values are set to null or system missing This is because unlike some applications does not allow mixed storage types within a field To avoid this any fields with mixed data should be read in as strings by changing the storage type in the source node or external application as necessary Reading empty strings from Oracle When reading from
150. dit or add a server connection in the Server Login dialog box By clicking Add you can access an empty Add Edit Server dialog box in which you can enter server connection details By selecting an existing connection and clicking Edit in the Server Login dialog box the Add Edit Server dialog box opens with the details for that connection so that you can make any changes 15 IBM SPSS Modeler Overview Note You cannot edit a server connection that was added from IBM SPSS Collaboration and Deployment Services since the name port and other details are defined in IBM SPSS Collaboration and Deployment Services Figure 3 3 Server Login Add Edit Server dialog box fed Server Login Add Edit Server Server localhost Y Port 28049 Description Doo O T Ensure secure connection use SSL 21 cance nee To Add Server Connections On the Tools menu click Server Login The Server Login dialog box opens In this dialog box click Add The Server Login Add Edit Server dialog box opens Enter the server connection details and click OK to save the connection and return to the Server Login dialog box m Server Specify an available server or select one from the list The server computer can be identified by an alphanumeric name for example myserver or an IP address assigned to the server computer for example 202 123 456 78 m Port Give the port number on which the server is listening If the default does no
151. e a copy of any encryption protected item the new item is automatically saved in an encrypted format using the original password unless you change the settings in the Encryption Options dialog box Loading Files You can reload a number of saved objects in IBM SPSS Modeler m Streams str m States cst m Models gm 91 Building Streams Models palette gen m Nodes nod Output cou m Projects cpj Opening New Files Streams can be loaded directly from the File menu gt On the File menu click Open Stream All other file types can be opened using the submenu items available on the File menu For example to load a model on the File menu click Models gt Open Model or Load Models Palette Opening Recently Used Files For quick loading of recently used files you can use the options at the bottom of the File menu Figure 5 43 Opening recently used options from the File menu sreams P mailshot4 Recent Projects gt Recent States fraud_graphschapter fraud_anomalies Export Stream Description fraud Exit newschancart_commented newschancart basklinks_Base modelingintro Select Recent Streams Recent Projects or Recent States to expand a list of recently used files Mapping Data Streams Using the mapping tool you can connect a new data source to a preexisting stream The mapping tool will not only set up the connection but it will also help you to specify how fields in
152. e added to the parent palette tab Figure 12 10 Subpalette creation on the Create Edit Sub Palette dialog box Create Edit Sub Palette Sub palette name Select available nodes to appear in the sub palette Nodes available Enterprise View Database Var File Fixed File To create a subpalette From the Tools menu open the Palette Manager Select the palette to which you want to add subpalettes Click the Sub Palettes button the Sub Palettes dialog box is displayed To the right of the Shown column click the Add Sub Palette button the Create Edit Sub Palette dialog box is displayed Type in a unique Sub palette name In the Nodes available area select the node to be added to the subpalette Click the Add Node right arrow button to move a selected node to the Selected nodes area When you have added the required nodes click OK to return to the Sub Palettes dialog box The subpalettes you create are displayed on the Nodes Palette when you select their parent palette tab For more information see the topic Changing a Palette Tab View on p 228 Changing a Palette Tab View Due to the large number of nodes available in IBM SPSS Modeler they may not all be visible on smaller screens without scrolling to the left or right of the Nodes Palette this is especially noticeable on the Modeling palette tab To reduce the need to scroll you can choose to display only the nodes contained in a subpa
153. e controls 247 Accessibility in IBM SPSS Modeler m Typing the first letter to find element in tree list When looking for an element in the categories pane extracted results pane or library tree you can type the first letter of the element when the pane has the focus This will select the next occurrence of an element beginning with the letter you entered Drop down lists In a drop down list for dialog boxes you can use the Spacebar to select an item and then close the list Additional tips for use are discussed at length in the following topics Interference with Other Software When testing IBM SPSS Modeler with screen readers such as JAWS our development team discovered that the use of a Systems Management Server SMS within your organization may interfere with JAWS ability to read Java based applications such as SPSS Modeler Disabling SMS will correct this situation Visit the Microsoft website for more information on SMS JAWS and Java Different versions of JAWS provide varying levels of support for Java based software applications Although IBM SPSS Modeler will work with all recent versions of JAWS some versions may have minor problems when used with Java based systems Visit the JAWS for Windows website at hittp www FreedomScientific com Using Graphs in IBM SPSS Modeler Visual displays of information such as histograms evaluation charts multiplots and scatterplots are difficult
154. e may approach NM This is rare most joins have many fewer matching keys If one data set is relatively larger than the other s or if the incoming data is already sorted by a key field then you can improve the performance of this node using the Optimization tab 234 Chapter 13 Aggregate When the Keys are contiguous option is not set this node reads but does not store its entire input data set before it produces any aggregated output In the more extreme situations where the size of the aggregated data reaches a limit determined by the SPSS Modeler Server configuration option Memory usage multiplier the remainder of the data set is sorted and processed as if the Keys are contiguous option were set When this option is set no data is stored because the aggregated output records are produced as the input data is read Distinct The Distinct node stores all of the unique key fields in the input data set in cases where all fields are key fields and all records are unique it stores the entire data set By default the Distinct node sorts the data on the key fields and then selects or discards the first distinct record from each group For smaller data sets with a low number of distinct keys or those that have been pre sorted you can choose options to improve the speed and efficiency of processing Type In some instances the Type node caches the input data when reading values the cache is used for downstream processing The cache
155. e node that you want to disable Click Disable Node on the pop up menu Alternatively you can click Node gt Disable Node on the Edit menu When you want to include the node back in the stream click Enable Node in the same way Note You can undo this action clicking Undo on the Edit menu or by pressing Ctrl Z You can undo this action clicking Undo on the Edit menu or by pressing Ctrl Z Adding Nodes in Existing Connections You can add a new node between two connected nodes by dragging the arrow that connects the two nodes 47 Building Streams Figure 5 8 Connecting a new node between two connected nodes Database Derive Type Table gt With the middle mouse button click and drag the connection arrow into which you want to insert the node Alternatively you can hold down the Alt key while clicking and dragging to simulate a middle mouse button Figure 5 9 New stream Aa Database Derive 4 Fifer Type onog Table gt Drag the connection to the node that you want to include and release the mouse button Note You can remove new connections from the node and restore the original by bypassing the node Deleting Connections between Nodes To delete the connection between two nodes gt Right click the connection arrow gt On the menu click Delete Connection 48 Chapter 5 Figure 5 10 Deleting the connection between nodes in a stream Filter Delete Connecti
156. e node the next time you run the data stream From then on the data is read from the cache which is stored on disk in a temporary directory rather than from the data source Caching is most useful following a time consuming operation such as a sort merge or aggregation For example suppose that you have a source node set to read sales data from a database and an Aggregate node that summarizes sales by location You can set up a cache on the Aggregate node rather than on the source node because you want the cache to store the aggregated data rather than the entire data set Note Caching at source nodes which simply stores a copy of the original data as it is read into IBM SPSS Modeler will not improve performance in most circumstances Nodes with caching enabled are displayed with a small document icon at the top right corner When the data is cached at the node the document icon is green 51 gt gt gt Building Streams Figure 5 12 Caching at the Type node to store newly derived fields COND1n Pressure Warnings Templne Powerline PowerFlux PoweyState type to_number to_string Discard fields Discard Initial TempChange PowerChange Outcome Outcome To Enable a Cache On the stream canvas right click the node and click Cache on the menu On the caching submenu click Enable You can turn the cache off by right clicking the node and clicking Disable on the caching sub
157. e of all values for a field across the entire data set Blanks and null Used to access flag and frequently fill user specified blanks or system missing values For example BLANK FIELD is used to raise a true flag for records where blanks are present Special fields Used to denote the specific fields under examination For example FIELD is used when deriving multiple fields Conventions in Function Descriptions The following conventions are used throughout this guide when referring to items in a function Convention Description BOOL A Boolean or flag such as true or false NUM NUM1 NUM2 Any number REAL REALI REAL2 Any real number such as 1 234 or 77 01 134 Chapter 8 Convention Description INT INT1 INT2 Any integer such as 1 or 77 CHAR A character code such as A STRING A string such as referrerlD LIST A list of items such as abc def ITEM A field such as Customer or extract_concept DATE A date field such as start_date where values are in a format such as DD MON YYYY TIME A time field such as power_flux where values are in a format such as HHMMSS Functions in this guide are listed with the function in one column the result type integer string and so on in another and a description where available in a third column For example the following is the descrip
158. e on Discarding Records When using a Select node to discard records note that syntax uses three valued logic and automatically includes null values in select statements To exclude null values system missing in a select expression you must explicitly specify this by using and not in the expression For example to select and include all records where the type of prescription drug is Drug C you would use the following select statement Drug drugC and not NULL Drug Earlier versions of excluded null values in such situations Chapter 7 Building CLEM Expressions About CLEM The Control Language for Expression Manipulation CLEM is a powerful language for analyzing and manipulating the data that flows along IBM SPSS Modeler streams Data miners use CLEM extensively in stream operations to perform tasks as simple as deriving profit from cost and revenue data or as complex as transforming web log data into a set of fields and records with usable information CLEM is used within SPSS Modeler to m Compare and evaluate conditions on record fields Derive values for new fields Derive new values for existing fields Reason about the sequence of records Insert data from records into reports Scripting A subset of the CLEM language can also be used when scripting in the user interface This allows you to perform many of the same data manipulations in an automated fashion CLEM expressions are indispensable for data p
159. e on the menu On the caching submenu click Load Cache In the Load Cache dialog box browse to the location of the cache file select it and click Load Previewing Data in Nodes To ensure that data is being changed in the way you expect as you build a stream you could run your data through a Table node at each significant step To save you from having to do this you can generate a preview from each node that displays a sample of the data that will be created thereby reducing the time it takes to build each node For nodes upstream of a model nugget the preview shows the input fields for a model nugget or nodes downstream of the nugget except terminal nodes the preview shows input and generated fields The default number of rows displayed is 10 however you can change this in the stream properties For more information see the topic Setting general options for streams on p 55 53 Building Streams Figure 5 13 Data Preview from a model nugget Preview from taxable_value Node 10 fields 10 records Fie 3 Edt Generate ar built volume _interior volume_other lot_size taxable_value XR taxable_value XRE taxable_value 1 pet 166 11 100 90500 105523 184 1526 604 a bss 603 73 497 420000 355497 802 14929 477 3 bez 303 75 91 152500 147713 631 1733 849 4 p26 228 12 55 92000 69313 952 8116 212 5 bss 666 441 390000 367551 491 16353 591 6 b7o 563 60 800 435000 395173 708 4759 398 7 02 355 4 130000 10986
160. e string length is less than or equal to the specified length then it is unchanged startstring LENGTH STRING String Equivalent to locchar CHAR 1 STRING It returns an integer substring indicating the point at which CHAR first occurs or 0 If the function has an invalid offset for example an offset that is beyond the length of the string this function returns null strmember CHAR STRING Integer Returns the Nth character CHAR of the input string STRING This function can also be subscrs N STRING CHAR written in a shorthand form as STRING N For example lowertoupper name 1 is a valid expression Returns a string SUBSTRING which consists substring N LEN STRING String of the LEN characters of the string STRING starting from the character at subscript N Returns the substring of STRING which substring_between N1 N2 STRING String begins at subscript N and ends at subscript N2 Removes leading and trailing white space trim STRING String characters from the specified string Removes leading white space characters trim_start STRING String from the specified string trimend STRING String Removes trailing white space characters from the specified string 146 Chapter 8 Function Result Description unicode_char NUM CHAR Returns the character with Unicode value NUM unicode_value CHAR NUM Returns the Unicode value of CHAR Inpu
161. e time in months from the baseline date to the date or timestamp represented by DATE as a real number This is an approximate figure based on a month of 30 4375 days If DATE is before the baseline date this function returns a negative number You must include a valid date for the calculation to work appropriately For example you should not specify 29 February 2001 as the date Because 2001 is a not a leap year this date does not exist 148 Chapter 8 Function Result Description Returns the time in weeks from the baseline date to the date or timestamp represented by DATE as a real number This is based on a week of 7 0 days If DATE is before the baseline date this function returns a date_in_weeks DATE Real negative number You must include a valid date for the calculation to work appropriately For example you should not specify 29 February 2001 as the date Because 2001 is a not a leap year this date does not exist Returns the time in years from the baseline date to the date or timestamp represented by DATE as a real number This is an approximate figure based on a year of 365 25 days If DATE is before the baseline date_in_years DATE Real date this function returns a negative number You must include a valid date for the calculation to work appropriately For example you should not specify 29 February 2001 as the date Because 2001 is a not a leap year this d
162. e time in weeks from the date or timestamp represented by DATE to that represented by DATE2 Real as a real number This is based on a week of 7 0 days If DATE2 is before DATE this function returns a negative number date_weeks_difference DATE1 DATE2 Returns the time in years from the date or timestamp represented by DATE to that represented by DATE2 aoe DATEI Real as a real number This is an approximate figure based on a year of 365 25 days If DATE2 is before DATE this function returns a negative number Returns a value of true if TIME represents a time time_before TIME1 TIME2 Boolean or timestamp before that represented by TIME2 Otherwise this function returns a value of 0 Returns the time difference in hours between the times or timestamps represented by TIME and TIME2 as time_hours_difference TIME a real number If you select Rollover days mins in the TIME Real stream properties dialog box a higher value of TIME1 is taken to refer to the previous day If you do not select the rollover option a higher value of TIME causes the returned value to be negative Returns the time in hours represented by TIME as a real number For example under time format HHMM time_in_hours TIME Real the expression time_in_hours 0130 evaluates to 1 5 TIME can represent a time or a timestamp Returns the time in minutes represented by TIME time_in_mins TIME Real as areal number TIME can rep
163. ea cscs ni cera eena e E a by atgaig ate ale gad ade ddeabeacans 6 Handling Missing Values 99 Overview of Missing Values 00 ccc tenet ete en eens Handling Missing Values 0 0 0 0 0c ccc ce eee e nen tenn eens 400 Handling Records with Missing Values nananana nanana 404 Handling Fields with Missing Values 0 0 0 0 cece cece eee eee eens 404 Imputing or Filling Missing Values 0 0 0 0 nananana 402 CLEM Functions for Missing Values 0 0 cc nananana 402 7 Building CLEM Expressions 105 About CURMI raaa seca EEE E a A a EA tea tabace Mae E O E A AA E E AER CLEM Examples oe sts ecco fete a2 Magee TE Gat anaphase ew a E Gos Cate ace EEE E 4 Values and Data TypeS ecs 0 ccc ee ia bai ai aaa e tent RERE Expressions and Conditions 0 0 ccc cece cect tne tenet nen nee Stream Session and SuperNode Parameters 0 000 cc cece eee ee eee ee eens Working with Strings 0 cc cece tenet ene nett nets Handling Blanks and Missing Values 00 cc cece cee cee tence ene eeenes Working with Numbers 0 0 0 0 ccc ccc een ee ent n ene e tent eens Working with Times and Dates 0 0 0 ccc een tenet n tenes Summarizing Multiple Fields 1 0 anan Working with Multiple Response Data 0 0 cece ccc cee nee eee n eens The Expression Builder 0 0 0 ce ee ene n tenet ene n eens Accessing the Expression Builder 1 0 0 0 0 ccc ccc eee nents Creat
164. eatly enhanced accessibility for all users as well as specific support for users with visual and other functional impairments This section describes the features and methods of working using accessibility enhancements such as screen readers and keyboard shortcuts Types of Accessibility Support Whether you have a visual impairment or are dependent on the keyboard for manipulation there is a wide variety of alternative methods for using this data mining toolkit For example you can build streams specify options and read output all without using the mouse Available keyboard shortcuts are listed in the topics that follow Additionally IBM SPSS Modeler provides extensive support for screen readers such as JAWS for Windows You can also optimize the color scheme to provide additional contrast These types of support are discussed in the following topics Accessibility for the Visually Impaired gt gt gt gt There are a number of properties you can specify in IBM SPSS Modeler that will enhance your ability to use the software Display Options You can select colors for the display of graphs You can also choose to use your specific Windows settings for the software itself This may help to increase visual contrast To set display options on the Tools menu click User Options Click the Display tab The options on this tab include the software color scheme chart colors and font sizes for nodes Use of Sounds f
165. ed analytics embedded in the product you can discover previously hidden patterns and trends in your data You can model outcomes and understand the factors that influence them enabling you to take advantage of business opportunities and mitigate risks SPSS Modeler is available in two editions SPSS Modeler Professional and SPSS Modeler Premium For more information see the topic IBM SPSS Modeler Editions on p B Copyright IBM Corporation 1994 2012 1 2 Chapter 1 IBM SPSS Modeler Server SPSS Modeler uses a client server architecture to distribute requests for resource intensive operations to powerful server software resulting in faster performance on larger data sets SPSS Modeler Server is a separately licensed product that runs continually in distributed analysis mode on a server host in conjunction with one or more IBM SPSS Modeler installations In this way SPSS Modeler Server provides superior performance on large data sets because memory intensive operations can be done on the server without downloading data to the client computer IBM SPSS Modeler Server also provides support for SQL optimization and in database modeling capabilities delivering further benefits in performance and automation IBM SPSS Modeler Administration Console The Modeler Administration Console is a graphical application for managing many of the SPSS Modeler Server configuration options which are also configurable
166. ed apply only to the current stream Click this button to set these options as the default for all streams Setting number format options for streams These options specify the format to use for various numeric expressions in the current stream Figure 5 18 Setting number format options for a stream O Stream1 X Select a setting These settings control the format of numeric expressions in the current stream Click Save As Default to use these General settings as the default for all your streams Date Time Number formats Number display format Optimization Standard decimal places Logging and Status Scientific decimal places Layout Currency decimal places Calculations in Radians Degrees CLEM Trigonometric functions only Number display format You can choose from standard 4 scientific 4 4 E or currency display formats 60 Chapter 5 Decimal places standard scientific currency For number display formats specifies the number of decimal places to be used when displaying or printing real numbers This option is specified separately for each display format Calculations in Select Radians or Degrees as the unit of measurement to be used in trigonometric CLEM expressions For more information see the topic Irigonometric Functions in Chapter 8 on p 139 Save As Default The options specified apply only to the current stream Click this button to set these options
167. ee the topic Summarizing Multiple Fields in Chapter 7 on p MS Returns a list a field names matching a specified pattern A question mark can be included in the pattern to match exactly one character an asterisk matches zero or more characters To FIELDS_MATCHING pattern Any match a literal question mark or asterisk rather than using these as wildcards a backslash can be used as an escape character For more information see the topic Summarizing Multiple Fields in Chapter 7 on p 115 Returns the list of fields in the named multiple response set For more information see the MULTI_RESPONSE_SET Any topic Working with Multiple Response Data in Chapter 7 on p 117 Chapter 9 Using IBM SPSS Modeler with a Repository About the IBM SPSS Collaboration and Deployment Services Repository IBM SPSS Modeler can be used in conjunction with an IBM SPSS Collaboration and Deployment Services repository enabling you to manage the life cycle of data mining models and related predictive objects and enabling these objects to be used by enterprise applications tools and solutions SPSS Modeler objects that can be shared in this way include streams nodes stream outputs scenarios projects and models Objects are stored in the central repository from where they can be shared with other applications and tracked using extended ve
168. een If a palette node has focus moves between nodes in the palette If a subpalette has focus moves between other subpalettes for this palette tab Alt Left Right Arrow Moves selected nodes and comments on the stream canvas horizontally in the direction of the arrow key Alt Up Down Arrow Moves selected nodes and comments on the stream canvas vertically in the direction of the arrow key Ctrl A Selects all nodes in a stream Ctr1 Q When a node has focus selects it and all nodes downstream and deselects all nodes upstream Ctrl W When a selected node has focus deselects it and all selected nodes downstream Ctrl Alt D Duplicates a selected node 240 Appendix A Shortcut Key Function Ctrl Alt L When a model nugget is selected in the stream opens an Insert dialog box to enable you to load a saved model from a nod file into the stream Ctrl Alt R Displays the Annotations tab for a selected node enabling you to rename the node Ctrl Alt U Creates a User Input source node Ctrl Alt C Toggles the cache for a node on or off Ctrl Alt F Flushes the cache for a node Tab On the stream canvas cycles through all the source nodes and comments in the current stream On a node palette moves between nodes in the palette On a selected subpalette moves to the first node in the subpalette Shift Tab Performs the same operation as Tab but in reverse order Ctrl Tab With f
169. eferences to its components Note The files added to a project are not saved in the project file itself Rather a reference to the files is stored in the project This means that moving or deleting a file will remove that object from the project Annotating a Project gt gt gt The project pane provides a number of ways to annotate your data mining efforts Project level annotations are often used to track big picture goals and decisions while folder or node annotations provide additional detail The Annotations tab provides enough space for you to document project level details such as the exclusion of data with irretrievable missing data or promising hypotheses formed during data exploration To annotate a project Select the project folder in either CRISP DM or Classes view Right click the folder and click Project Properties Click the Annotations tab 207 gt Projects and Reports Figure 11 6 Annotations tab in the project properties dialog box i Mortgage Retention Project Keywords Uses predictive modeling to determine which mortgage customers are likely to churn at the end of their discounted period which customers will switch to a new rate and which will stay inert Created on February 8 2004 5 19 PM by sdunworth ID ray Last saved as C temp projectiMortgage Retention Mortgage Retention Project cpj on June 25 2009 2 46 PM by djones Lo canca ase eest Enter keywo
170. elected a group of functions double click to insert the functions into the expression field at the point indicated by the position of the cursor Selecting Fields Parameters and Global Variables The field list displays all fields available at this point in the data stream Scroll to select a field from the list Double click or click the yellow arrow button to add a field to the expression Figure 7 8 Expression Builder Fields list Expression Builder Na_to_K Formula Multi Response Set Boolean r Recently Used Boolean F Boolean Boolean Real Boolean Real Boolean String Boolean 2 to Unknown Integer is_integer ITEM Returns a value of true if ITEM type is an integer Otherwise returns a value of false iM Check expression before saving ob canoe For more information see the topic Stream Session and SuperNode Parameters on p 1121 In addition to fields you can also choose from the following items Multiple response sets For more information see the JBM SPSS Modeler Source Process and Output Nodes guide Recently used contains a list of fields multiple response sets parameters and global values used within the current session Parameters For more information see the topic Stream Session and SuperNode Parameters on p MIZ Global values For more information see the IBM SPSS Modeler Source Process and Output Nodes guide 122 Cha
171. en an arrow key The following keyboard shortcuts are now available Shortcut Key Function Arrow key Moves focus between individual cells in the grid The cell distribution display in the right hand pane changes as the focus moves Ctrl comma Selects or deselects the entire column in the grid in which a cell has focus To add a column to the selection use the arrow keys to navigate to a cell in that column and press Ctrl again Tab Moves focus out of the grid and onto the next screen control Shift Tab Moves focus out of the grid and back to the previous screen control F2 Enters edit mode label and description cells only Enter Saves editing changes and exits edit mode label and description cells only Esc Exits edit mode without saving changes label and description cells only Shortcut Keys Example Building Streams gt gt gt To make the stream building process more clear for users dependent on the keyboard or on a screen reader following is an example of building a stream without the use of the mouse In this example you will build a stream containing a Variable File node a Derive node and a Histogram node using the following steps Start SPSS Modeler When IBM SPSS Modeler first starts focus is on the Favorites tab of the node palette Ctrl Down Arrow Moves focus from the tab itself to the body of the tab Right Arrow Moves focus to the Variable F
172. enerates a decision tree that allows you to predict or classify future observations The method uses recursive partitioning to split the training records into segments by minimizing the impurity at each step where a node in the tree is considered pure if 100 of cases in the node fall into a specific category of the target field Target and input fields can be numeric ranges or categorical nominal ordinal or flags all splits are binary only two subgroups The QUEST node provides a binary classification method for building decision trees designed to reduce the processing time required for large C amp R Tree analyses while also reducing the tendency found in classification tree methods to favor inputs that allow more splits Input fields can be numeric ranges continuous but the target field must be categorical All splits are binary The CHAID node generates decision trees using chi square statistics to identify optimal splits Unlike the C amp R Tree and QUEST nodes CHAID can generate nonbinary trees meaning that some splits have more than two branches Target and input fields can be numeric range continuous or categorical Exhaustive CHAID is a modification of CHAID that does a more thorough job of examining all possible splits but takes longer to compute The C5 0 node builds either a decision tree or a rule set The model works by splitting the sample based on the field that provides the maximum information gain at each level
173. er The result of this operation is the bitwise inclusive or of INT and INT2 That is there is a 1 in the result for each bit position for which there is a 1 in either INTI or INT2 or both INT1 amp INT2 Integer The result of this operation is the bitwise exclusive or of INTI and INT2 That is there is a 1 in the result for each bit position for which there is a 1 in either INTI or INT2 but not in both INT1 amp amp INT2 Integer Produces the bitwise and of the integers INTI and INT2 That is there is a 1 in the result for each bit position for which there is a 1 in both JNT and INT2 INT1 amp amp INT2 Integer Produces the bitwise and of JNT and the bitwise complement of JNT2 That is there is a 1 in the result for each bit position for which there is a 1 in INT and a 0 in INT2 This is the same as INT1 amp amp INT2 and is useful for clearing bits of INTI set in INT2 INT lt lt N Integer Produces the bit pattern of INTI shifted left by N positions A negative value for N produces a right shift INT gt N Integer Produces the bit pattern of INTI shifted right by N positions A negative value for N produces a left shift INT1 amp amp _0 INT2 Boolean Equivalent to the Boolean expression INT1 amp amp INT2 0 but is more efficient INT1 amp amp _0 INT2 Boolean Equivalent to the Boolean expression INT1 amp amp
174. er a project folder This is useful in CRISP DM view for example to provide a quick overview of each phase s goals or to mark the status of a phase such as In progress or Complete Annotation field Use this field for more lengthy annotations that can be collated in the project report The CRISP DM view includes a description of each data mining phase in the annotation but you should feel free to customize this for your own project Include in report To include the annotation in reports select Include in report Object Properties You can view object properties and choose whether to include individual objects in the project report To access object properties gt Right click an object in the project pane gt On the menu click Object Properties Figure 11 8 Object properties dialog box e MortgageRetention Name MortgageRetention Path ect Mortgage 20Retention MortgageRetention str M Include in report 2 Name This area lists the name of the saved object Path This area lists the location of the saved object Include in report Select this option to include the object details in a generated report 209 Projects and Reports Closing a Project When you exit IBM SPSS Modeler or open a new project the existing project file cpj is closed Some files associated with the project such as streams nodes or graphs may still be open If you want to leave these files open re
175. er different values for the same parameter on different occasions you can specify runtime prompts for one or more stream or session parameter values Figure 5 26 Runtime prompting for parameter values e Specify Session Parameters Minimum value Maximum value 75 F Turn off these prompts turn back on in Stream Properties C ore C Parameters Optional Enter a value for the parameter or leave the default value if there is one Turn off these prompts Select this box if you do not want these prompts to be displayed when you run the stream You can cause them to be redisplayed by selecting the Prompt check box on the stream properties or session properties dialog box where the parameters were defined For more information see the topic Setting Stream and Session Parameters on p 68 Specifying Value Constraints for a Parameter Type You can make value constraints for a parameter available during stream deployment to an external application that reads data modeling streams This dialog box allows you to specify the values available to an external user running the stream Depending on the data type value constraints vary dynamically in the dialog box The options shown here are identical to the options available for values from the Type node 71 Building Streams Figure 5 27 Specifying available values for a parameter MinValue Values Type Continuous Storage integer
176. erived fields that effectively summarizes the information in the original set of fields The Feature Selection node screens input fields for removal based on a set of criteria such as the percentage of missing values it then ranks the importance of remaining inputs relative to a specified target For example given a data set with hundreds of potential inputs which are most likely to be useful in modeling patient outcomes Discriminant analysis makes more stringent assumptions than logistic regression but can be a valuable alternative or supplement to a logistic regression analysis when those assumptions are met Logistic regression is a statistical technique for classifying records based on values of input fields It is analogous to linear regression but takes a categorical target field instead of a numeric range The Generalized Linear model expands the general linear model so that the dependent variable is linearly related to the factors and covariates through a specified link function Moreover the model allows for the dependent variable to have a non normal distribution It covers the functionality of a wide number of statistical models including linear regression logistic regression loglinear models for count data and interval censored survival models A generalized linear mixed model GLMM extends the linear model so that the target can have a non normal distribution is linearly related to the factors and covariates via a specif
177. ermining which method to use you should also consider the measurement level of fields with missing values Numeric fields For numeric field types such as Continuous you should always eliminate any non numeric values before building a model because many models will not function if blanks are included in numeric fields Categorical fields For categorical fields such as Nominal and Flag altering missing values is not necessary but will increase the accuracy of the model For example a model that uses the field Sex will still function with meaningless values such as Y and Z but removing all values other than M and F will increase the accuracy of the model 102 Chapter 6 Screening or Removing Fields To screen out fields with too many missing values you have several options m You can use a Data Audit node to filter fields based on quality m You can use a Feature Selection node to screen out fields with more than a specified percentage of missing values and to rank fields based on importance relative to a specified target m Instead of removing the fields you can use a Type node to set the field role to None This will keep the fields in the data set but exclude them from the modeling processes Imputing or Filling Missing Values In cases where there are only a few missing values it may be useful to insert values to replace the blanks You can do this from the Data Audit report which allows you to specify options for spe
178. escribe a stream to others in your organization To help you do this you can attach explanatory comments to streams nodes and model nuggets 79 Building Streams Figure 5 34 Stream with comments added NewsChan say Ne soni S f NEWSCHAN Table Others can then view these comments on screen or you can print out an image of the stream that includes the comments You can list all the comments for a stream or SuperNode change the order of comments in the list edit the comment text and change the foreground or background color of a comment For more information see the topic Listing Stream Comments on p 84 You can also add notes in the form of text annotations to streams nodes and nuggets by means of the Annotations tab of a stream properties dialog box a node dialog box or a model nugget window These notes are visible only when the Annotations tab is open except that stream annotations can also be shown as on screen comments For more information see the topic Annotations on p 86 Comments Comments take the form of text boxes in which you can enter any amount of text and you can add as many comments as you like A comment can be freestanding not attached to any stream objects or it can be connected to one or more nodes or model nuggets in the stream Freestanding comments are typically used to describe the overall purpose of the stream connected comments describe the node or nugget t
179. ese settings control the format of date and time expressions in the current stream Click Save As Default to use these General settings as the default for all your streams Number formats Import date time as Date Time O String Optimization Date format Logging and Status Time format 4H MIM SS Rollover days mins Layout Date baseline 1st Jan 2 digit dates start from 1930 Import date time as Select whether to use date time storage for date time fields or whether to import them as string variables Date format Select a date format to be used for date storage fields or when strings are interpreted as dates by CLEM date functions Time format Select a time format to be used for time storage fields or when strings are interpreted as times by CLEM time functions Rollover days mins For time formats select whether negative time differences should be interpreted as referring to the previous day or hour Date baseline 1st Jan Select the baseline years always 1 January to be used by CLEM date functions that work with a single date 59 Building Streams 2 digit dates start from Specify the cutoff year to add century digits for years denoted with only two digits For example specifying 1930 as the cutoff year will assume that 05 11 02 is in the year 2002 The same setting will use the 20th century for dates after 30 thus 05 11 73 is assumed to be in 1973 Save As Default The options specifi
180. ession in which the parameter value is specified in the script The scope of a parameter depends on where it is set m Stream parameters can be set in a stream script or in the stream properties dialog box and they are available to all nodes in the stream They are displayed on the Parameters list in the Expression Builder m Session parameters can be set in a stand alone script or in the session parameters dialog box They are available to all streams used in the current session all streams listed on the Streams tab in the managers pane Parameters can also be set for SuperNodes in which case they are visible only to nodes encapsulated within that SuperNode Using Parameters in CLEM Expressions Parameters are represented in CLEM expressions by P pname where pname is the name of the parameter When used in CLEM expressions parameters must be placed within single quotes for example P scale Available parameters are easily viewed using the Expression Builder To view current parameters gt In any dialog box accepting CLEM expressions click the Expression Builder button gt From the Fields list select Parameters You can select parameters from the list for insertion into the CLEM expression For more information see the topic Selecting Fields Parameters and Global Variables on p 21 Working with Strings There are a number of operations available for strings including m Converting a string
181. etting options 217 welcome dialog box 220 white space removing from strings I12 41 zooming 21
182. eturns true for all records whose type is an integer is_number ITEM Boolean Returns true for all records whose type is a number is_real ITEM Boolean Returns true for all records whose type is a real is_string ITEM Boolean Returns true for all records whose type is a string is_time ITEM Boolean Returns true for all records whose type is a time is_timestamp ITEM Boolean Returns true for all records whose type is a timestamp 135 CLEM Language Reference Conversion Functions Conversion functions allow you to construct new fields and convert the storage type of existing files For example you can form new strings by joining strings together or by taking strings apart To join two strings use the operator gt lt For example if the field Site has the value BRAMLEY then xx gt lt Site returns xxBRAMLEY The result of gt lt is always a string even if the arguments are not strings Thus if field V1 is 3 and field V2 is 5 then V1 gt lt V2 returns 35 a string not a number Conversion functions and any other functions that require a specific type of input such as a date or time value depend on the current formats specified in the Stream Options dialog box For example if you want to convert a string field with values Jan 2003 Feb 2003 and so on select the matching date format MON YYYY as the default date format for the stream For more information see the topic Setting general options for strea
183. exist on the scoring branch only one can be designated Note that when the stream is initially created this may effectively be a placeholder model that is updated or regenerated as new data is available Deploy as stream Click this option if you want to use the stream with IBM SPSS Modeler Advantage or IBM SPSS Collaboration and Deployment Services and see note following Deploy as scenario Click this option if you want to use the stream with IBM SPSS Collaboration and Deployment Services or Predictive Applications version 5 and see note following Check Click this button to check whether this is a valid stream for deployment All streams must have a designated scoring node before they can be deployed If you are deploying as a scenario the stream must also contain a valid Enterprise View source node Error messages are displayed if these conditions are not satisfied Store Deploys the stream if it is valid If not an error message is displayed Click the Fix button correct the error and try again Preview Stream Description Enables you to view the contents of the stream description that SPSS Modeler creates for the stream For more information see the topic Stream Descriptions in Chapter 5 on p 74 Note Deploy as stream or scenario Multiple Enterprise View nodes can be used within the modeling branch If so using a single data connection for all Enterprise View nodes within the branch is preferable in
184. for example to see which nodes have the longest execution times Terminal Node The identifier of the branch to which the node belongs The identifier is the name of the terminal node at the end of the branch Node Label The name of the node to which the execution time refers Node Id The unique identifier of the node to which the execution time refers This identifier is generated by the system when the node is created Execution Time s The time in seconds taken to execute this node Setting Stream and Session Parameters Parameters can be defined for use in CLEM expressions and in scripting They are in effect user defined variables that are saved and persisted with the current stream session or SuperNode and can be accessed from the user interface as well as through scripting If you save a stream for example any parameters set for that stream are also saved This distinguishes them from local script variables which can be used only in the script in which they are declared Parameters are often used in scripting as part of a CLEM expression in which the parameter value is specified in the script The scope of a parameter depends on where it is set m Stream parameters can be set in a stream script or in the stream properties dialog box and they are available to all nodes in the stream They are displayed on the Parameters list in the Expression Builder m Session parameters can be set in a stand alone script or in the
185. fset values Additional sequence facilities For many applications each record passing through a stream can be considered as an individual case independent of all others In such situations the order of records is usually unimportant For some classes of problems however the record sequence is very important These are typically time series situations in which the sequence of records represents an ordered sequence of events or occurrences Each record represents a snapshot at a particular instant in time much of the richest information however might be contained not in instantaneous values but in the way in which such values are changing and behaving over time Of course the relevant parameter may be something other than time For example the records could represent analyses performed at distances along a line but the same principles would apply Sequence and special functions are immediately recognizable by the following characteristics m They are all prefixed by m Their names are given in upper case Sequence functions can refer to the record currently being processed by a node the records that have already passed through a node and even in one case records that have yet to pass through a node Sequence functions can be mixed freely with other components of CLEM expressions although some have restrictions on what can be used as their arguments Examples You may find it useful to know how long it has been since a certain
186. ften used to create clusters or segments that are then used as inputs in subsequent analyses for example by segmenting potential customers into homogeneous subgroups 39 Understanding Data Mining Segmentation nodes Lio The Auto Cluster node estimates and compares clustering models which identify e groups of records that have similar characteristics The node works in the same manner as other automated modeling nodes allowing you to experiment with multiple combinations of options in a single modeling pass Models can be compared using basic measures with which to attempt to filter and rank the usefulness of the cluster models and provide a measure based on the importance of particular fields AEN The K Means node clusters the data set into distinct groups or clusters The method R defines a fixed number of clusters iteratively assigns records to clusters and adjusts Nn the cluster centers until further refinement can no longer improve the model Instead of trying to predict an outcome k means uses a process known as unsupervised learning to uncover patterns in the set of input fields yo The Kohonen node generates a type of neural network that can be used to cluster the data set into distinct groups When the network is fully trained records that are T similar should be close together on the output map while records that are different will be far apart You can look at the number of observations captured by each
187. g SUBSTRING then this function returns the subscript 1 Otherwise this function returns a value of 0 isstartstring SUBSTRING STRING Integer Searches the string STRING starting from its Nth character for a substring equal to the string SUBSTRING If found this function issubstring SUBSTRING N STRING Integer returns the integer subscript at which the matching substring begins Otherwise this function returns a value of 0 If N is not given this function defaults to 1 Searches the string STRING starting from its Nth character for a substring equal to the string SUBSTRING If found this function issubstring SUBSTRING STRING Integer returns the integer subscript at which the matching substring begins Otherwise this function returns a value of 0 If N is not given this function defaults to 1 Returns the index of the Nth occurrence of SUBSTRING within the specified STRING If there are fewer than N occurrences of SUBSTRING 0 is returned issubstring_count SUBSTRING N STRING Integer This function is the same as issubstring but the match is constrained to start on or before the subscript STARTLIM and to end on or before the subscript EVDLIM Integer The STARTLIM or ENDLIM constraints may be disabled by supplying a value of false for either argument for example issubstring_lim SUBSTRING N false false STRING is the same as issubstring issubstring_lim SUBSTRING N STARTLIM ENDLIM STRI
188. g options storing in the IBM SPSS Collaboration and Deployment Services Repository 71 noisy data B1 normal distribution probability functions 139 not equal operator not operator 137 notifications setting options 217 nuggets 78 defined 20 NULL function I02 34 156 nulls 99 113 number display formats B9 numbers 114 numeric functions 138 object properties IBM SPSS Collaboration and Deployment Services Repository 180 257 objects properties 208 OFFSET function 152 OFFSET function 150 152 performance considerations 234 oneof function 41 opening models 90 nodes 90 output PO projects 202 states DO streams 90 operator precedence 31 operators in CLEM expressions joining strings 135 optimization 60 options 215 display 220 for IBM SPSS Modeler 215 mitts 55 57 59 60 63 stream properties user 217 or operator I37 output 19 output files saving 89 output nodes 2 output objects storing in the IBM SPSS Collaboration and Deployment Services Repository 171
189. g with on screen comments you can use the following shortcuts Shortcut Key Function Alt C Toggles the show hide comment feature Alt M Inserts a new comment if comments are currently displayed shows comments if they are currently hidden Tab On the stream canvas cycles through all the source nodes and comments in the current stream Enter When a comment has focus indicates the start of editing Alt Enter or Ctrl Tab Ends editing and saves editing changes Esc Cancels editing Changes made during editing are lost Alt Shift Up Arrow Reduces the height of the text area by one grid cell or one pixel if snap to grid is on or off Alt Shift Down Arrow Increases the height of the text area by one grid cell or one pixel if snap to grid is on or off Alt Shift Left Arrow Reduces the width of the text area by one grid cell or one pixel if snap to grid is on or off Alt Shift Right Arrow Increases the width of the text area by one grid cell or one pixel if snap to grid is on or off Shortcuts for Cluster Viewer and Model Viewer Shortcut keys are available for navigating around the Cluster Viewer and Model Viewer windows General Cluster Viewer and Model Viewer Shortcut Key Function Tab Moves focus to the next screen control Shift Tab Moves focus to the previous screen control Down Arrow If a drop down list has focus opens the list or
190. ges needed to print a stream 26 Chapter 3 Using the Mouse in IBM SPSS Modeler The most common uses of the mouse in IBM SPSS Modeler include the following m Single click Use either the right or left mouse button to select options from menus open pop up menus and access various other standard controls and options Click and hold the button to move and drag nodes Double click Double click using the left mouse button to place nodes on the stream canvas and edit existing nodes m Middle click Click the middle mouse button and drag the cursor to connect nodes on the stream canvas Double click the middle mouse button to disconnect a node If you do not have a three button mouse you can simulate this feature by pressing the Alt key while clicking and dragging the mouse Using Shortcut Keys Many visual programming operations in IBM SPSS Modeler have shortcut keys associated with them For example you can delete a node by clicking the node and pressing the Delete key on your keyboard Likewise you can quickly save a stream by pressing the S key while holding down the Ctrl key Control commands like this one are indicated by a combination of Ctrl and another key for example Ctrl S There are a number of shortcut keys used in standard Windows operations such as Ctrl X to cut These shortcuts are supported in SPSS Modeler along with the following application specific shortcuts Note In some cases old shortcut ke
191. get The nugget must already be on the scoring branch for this to be possible If you turn off the refresh model status of a nugget this is equivalent to setting the deployment type of the stream to Scoring Only and the Deployment tab of the stream properties dialog box is updated accordingly You can turn this status on and off by means of the Use as Refresh Model option on the pop up menu of the nugget on the current scoring branch Removing the model link of a nugget on the scoring branch also removes the refresh model status of the nugget You can undo removal of the model link by means of the Edit menu or the toolbar doing so also reinstates the refresh model status of the nugget How the Refresh Model is Selected As well as the scoring branch the link to the refresh model is also highlighted in the stream The model nugget chosen as the refresh model and therefore the link that is highlighted depends on how many nuggets are in the stream 191 Using IBM SPSS Modeler with a Repository Single Model in Stream Figure 9 28 Scoring branch with single model in the stream pm_customer_train1 s Type Select esponse 38 2 5 Enterprise View Type response Analysis i jaa Ate If a single linked model nugget is on the scoring branch when it is identified as such that nugget becomes the refresh model for the stream Multiple Models in Stream If there is more than one
192. gram installation see Application Examples on p 5 Working with Nodes Nodes are used in IBM SPSS Modeler to help you explore data Various nodes in the workspace represent different objects and actions The palette at the bottom of the SPSS Modeler window contains all of the possible nodes used in stream building There are several types of nodes Source nodes bring data into the stream and are located on the Sources tab of the nodes palette Process nodes perform operations on individual data records and fields and can be found in the Record Ops and Field Ops tabs of the palette Output nodes produce a variety of output for data charts and model results and are included on the Graphs Output and Export tabs of the nodes palette Modeling nodes use statistical algorithms to create model nuggets and are located on the Modeling tab and if activated the Database Modeling tab of the nodes palette For more information see the topic Nodes Palette in Chapter 3 on p 18 You connect the nodes to form streams which when run let you visualize relationships and draw conclusions Streams are like scripts you can save them and reuse them with different data files 43 Building Streams A runnable node that processes stream data is known as a terminal node A modeling or output node is a terminal node if it is located at the end of a stream or stream branch You cannot connect further nodes to a termi
193. group Note To export to a Microsoft Office file you must have the corresponding application installed Title Specify a title for the report Report structure Select either CRISP DM or Classes CRISP DM view provides a status report with big picture synopses as well as details about each phase of data mining Classes view is an object based view that is more appropriate for internal tracking of data and streams Author The default user name is displayed but you can change it Report includes Select a method for including objects in the report Select all folders and objects to include all items added to the project file You can also include items based on whether Include in Report is selected in the object properties Alternatively to check on unreported items you can choose to include only items marked for exclusion where Include in Report is not selected Select This option allows you to provide project updates by selecting only recent items in the report Alternatively you can track older and perhaps unresolved issues by setting parameters for old items Select all items to dismiss time as a parameter for the report Order by You can select a combination of the following object characteristics to order them within a folder m Type Group objects by type m Name Organize objects alphabetically m Added date Sort objects using the date they were added to the project Saving and Exporting Generated Reports A repo
194. gt c Similarly the following expression is stripchar 3 123 gt 12 It is important to note that characters are always encapsulated within single backquotes Combining Functions in an Expression Frequently CLEM expressions consist of a combination of functions The following function combines subscr and lowertoupper to return the first character of produce_ID and convert it to upper case lowertoupper subscr 1 produce_ID gt C This same expression can be written in shorthand as lowertoupper produce_ID 1 gt C Another commonly used combination of functions is locchar_back n length web_page web_page This expression locates the character n within the values of the field web_page reading backward from the last character of the field value By including the length function as well the expression dynamically calculates the length of the current value rather than using a static number such as 7 which will be invalid for values with less than seven characters Special Functions Numerous special functions preceded with an symbol are available Commonly used functions include BLANK referrer ID gt T 110 Chapter 7 Frequently special functions are used in combination which is a commonly used method of flagging blanks in more than one field at a time BLANK FIELD gt T Additional examples are discussed throughout the CLEM documentation For more information
195. han one option to limit the search except that searching by node ID using the ID equals field excludes the other options Node label contains Check this box and enter all or part of a node label to search for a particular node Searches are not case sensitive and multiple words are treated as a single piece of text 74 Chapter 5 Node category Check this box and click a category on the list to search for a particular type of node Process Node means a node from the Record Ops or Field Ops tab of the nodes palette Apply Model Node refers to a model nugget Keywords include Check this box and enter one or more complete keywords to search for nodes having that text in the Keywords field on the Annotations tab of the node dialog box Keyword text that you enter must be an exact match Separate multiple keywords with semicolons to search for alternatives for example entering proton neutron will find all nodes with either of these keywords For more information see the topic Annotations on p 86 Annotation contains Check this box and enter one or more words to search for nodes that contain this text in the main text area on the Annotations tab of the node dialog box Searches are not case sensitive and multiple words are treated as a single piece of text For more information see the topic Annotations on p 86 Generates field called Check this box and enter the name of a generated field
196. hanges are periodically made to the information herein these changes will be incorporated in new editions of the publication IBM may make improvements and or changes in the product s and or the program s described in this publication at any time without notice Any references in this information to non IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk IBM may use or distribute any of the information you supply in any way it believes appropriate without incurring any obligation to you Licensees of this program who wish to have information about it for the purpose of enabling i the exchange of information between independently created programs and other programs including this one and ii the mutual use of the information which has been exchanged should contact IBM Software Group Attention Licensing 233 S Wacker Dr Chicago IL 60606 USA Copyright IBM Corporation 1994 2012 249 250 Appendix C Such information may be available subject to appropriate terms and conditions including in some cases payment of a fee The licensed program described in this document and all licensed material available for it are provided by IBM under terms of the IBM Customer Agreement IBM International Program License Agreement or any equi
197. hat does not infringe any IBM intellectual property right may be used instead However it is the user s responsibility to evaluate and verify the operation of any non IBM product program or service IBM may have patents or pending patent applications covering subject matter described in this document The furnishing of this document does not grant you any license to these patents You can send license inquiries in writing to IBM Director of Licensing IBM Corporation North Castle Drive Armonk NY 10504 1785 U S A For license inquiries regarding double byte character set DBCS information contact the IBM Intellectual Property Department in your country or send inquiries in writing to Intellectual Property Licensing Legal and Intellectual Property Law IBM Japan Ltd 1623 14 Shimotsuruma Yamato shi Kanagawa 242 8502 Japan The following paragraph does not apply to the United Kingdom or any other country where such provisions are inconsistent with local law INTERNATIONAL BUSINESS MACHINES PROVIDES THIS PUBLICATION AS IS WITHOUT WARRANTY OF ANY KIND EITHER EXPRESS OR IMPLIED INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF NON INFRINGEMENT MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE Some states do not allow disclaimer of express or implied warranties in certain transactions therefore this statement may not apply to you This information could include technical inaccuracies or typographical errors C
198. he Java Access Bridge which is installed along with SPSS Modeler If you have JAWS installed simply launch JAWS before launching SPSS Modeler to use this product Due to the nature of SPSS Modeler s unique graphical representation of the data mining process charts and graphs are optimally used visually It is possible however for you to understand and make decisions based on output and models viewed textually using a screen reader Note With 64 bit client machines some assistive technology features do not work This is because the Java Access Bridge is not designed for 64 bit operation Using the IBM SPSS Modeler Dictionary File An SPSS Modeler dictionary file Awt JDF is available for inclusion with JAWS To use this file gt Navigate to the accessibility subdirectory of your SPSS Modeler installation and copy the dictionary file Awt JDF gt Copy it to the directory with your JAWS scripts You may already have a file named Awt JDF on your machine if you have other JAVA applications running In this case you may not be able to use this dictionary file without manually editing the dictionary file Using a Screen Reader with HTML Output When viewing output displayed as HTML within IBM SPSS Modeler using a screen reader you may encounter some difficulties A number of types of output are affected including Output viewed on the Advanced tab for Regression Logistic Regression and Factor PCA nodes m Report node
199. he appropriate fields from the Essential Fields list 95 Building Streams To Set Essential Fields gt Right click the source node of the template stream that will be replaced gt On the menu click Data Mapping gt Specify Essential Fields Figure 5 48 Specifying essential fields Data mapping Essential fields for restored Specify fields essential for stream execution This ensures proper field matching if this node is replaced CardiD e Date E Amount gt Using the Field Chooser you can add or remove fields from the list To open the Field Chooser click the icon to the right of the fields list Examining Mapped Fields Once you have selected the point at which one data stream or data source will be mapped to another a dialog box opens for you to select fields for mapping or to ensure that the system default mapping is correct If essential fields have been set for the stream or data source and they are unmatched these fields are displayed in red Any unmapped fields from the data source will pass through the Filter node unaltered but note that you can map non essential fields as well Figure 5 49 Selecting fields for mapping Data mapping Map fields Map fields from Statistics File Select field to map to in the Mapped column Original customer _id E response E response_date E purchase purchase_date E product_id S response_date E Rowid purchase age purchase_date E age_y
200. he caching node and that the field values are read or set the string length by means of the default_sql_string_length parameter in the options cfg file Doing so ensures that the corresponding column in the temporary table is set to the correct width to accommodate the strings To take advantage of database caching both SQL optimization and database caching must be enabled Note that Server optimization settings override those on the Client For more information see the topic Setting optimization options for streams in Chapter 5 on p 60 With database caching enabled simply right click any nonterminal node to cache data at that point and the cache will be created automatically directly in the database the next time the stream is run If database caching or SQL optimization is not enabled the cache will be written to the file system instead 233 Performance Considerations for Streams and Nodes Note The following databases support temporary tables for the purpose of caching DB2 Netezza Oracle SQL Server and Teradata Other databases will use a normal table for database caching The SQL code can be customized for specific databases contact Support for assistance Performance Process Nodes Sort The Sort node must read the entire input data set before it can be sorted The data is stored in memory up to some limit and the excess is spilled to disk The sorting algorithm is a combination algorithm data is rea
201. he field named FIELD in the current record Used only in SINCE expressions THIS FIELD Any Global Functions The functions MEAN SUM MIN MAX and SDEV work on at most all of the records read up to and including the current one In some cases however it is useful to be able to work out how values in the current record compare with values seen in the entire data set Using a Set Globals node to generate values across the entire data set you can access these values in a CLEM expression using the global functions For example GLOBAL_MAX Age returns the highest value of Age in the data set while the expression Value GLOBAL_MEAN Value GLOBAL_SDEV Value expresses the difference between this record s Value and the global mean as a number of standard deviations You can use global values only after they have been calculated by a Set Globals node All current global values can be canceled by clicking the Clear Global Values button on the Globals tab in the stream properties dialog box Note functions cannot be called from scripts Function Result Description Returns the maximum value for FIELD over the whole data set as previously generated by a Set Globals node FIELD must be the name of a numeric field If the corresponding global value has not been set an error occurs Note that this function cannot be called from a script GLOBAL_MAX FIELD Number 156 Chap
202. he stream to save the comment To attach a comment to a node or nugget Select one or more nodes or nuggets on the stream canvas Do one of the following m On the main menu click Insert gt New Comment m Right click the stream background and click New Comment on the pop up menu m Click the New Comment button in the toolbar Enter the comment text Click another node in the stream to save the comment Alternatively you can Insert a freestanding comment see previous section Do one of the following m Select the comment press F2 then select the node or nugget m Select the node or nugget press F2 then select the comment m Three button mice only Move the mouse pointer over the comment hold down the middle button drag the mouse pointer over the node or nugget and release the mouse button To attach a comment to an additional node or nugget If a comment is already attached to a node or nugget or if it is currently at stream level and you want to attach it to an additional node or nugget do one of the following m Select the comment press F2 then select the node or nugget m Select the node or nugget press F2 then select the comment m Three button mice only Move the mouse pointer over the comment hold down the middle button drag the mouse pointer over the node or nugget and release the mouse button To edit an existing comment Do one of the following m Double click the comment text box m Select
203. here Warehouse Bulk loading for database export Additional help information is available for database bulk loading using an external loader program 9 New Features SOL generation enhancements The Aggregate node now supports SQL generation for date time timestamp and string data types in addition to integer and real With IBM Netezza databases the Sample node supports SQL generation for simple and complex sampling and the Binning node supports SQL generation for all binning methods except Tiles In database model scoring For IBM DB2 for z OS IBM Netezza and Teradata databases it is possible to enable SQL pushback of many of the model nuggets to carry out model scoring as opposed to in database mining within the database To do this you can install a scoring adapter into the database When you publish a model for the scoring adapter the model is enabled to use the user defined function UDF capabilities of the database to perform the scoring A new configuration option db_udf_enabled in options cfg causes the SQL generation option to generate UDF SQL by default New format for database connection in batch mode The format for specifying a database connection in batch mode has changed to a single argument to be consistent with the way it is specified in scripting Enhancements to SPSS Statistics integration On the Statistics Output node additional procedures are available on the Syntax tab through the Select a dialog b
204. his list to navigate there directly or navigate using the object list below this field Up Folder button Navigates to one level above the current folder in the hierarchy New Folder button Creates a new folder at the current level in the hierarchy File name The repository file name of the selected object To retrieve that object click Retrieve Files of type The type of object that you have chosen to retrieve Only objects of this type together with folders are shown in the object list To display objects of a different type for retrieval select the object type from the list Open as locked By default when an object is retrieved it is locked in the repository so that others cannot update it If you do not want the object to be locked on retrieval uncheck this box Description Keywords If additional details about the object were defined when the object was stored those details are displayed here For more information see the topic Adding Information About Stored Objects on p 165 Version To retrieve a version of the object other than the latest click this button Detailed information for all versions is displayed allowing you to choose the version you want Selecting an Object Version Figure 9 13 Selecting a version of an object Repository Select Version Version Label Size Creation Date Created By 0 2007 03 26 14 27 28 398 3KB Wed May 23 20 45 07 admin Inf
205. i Repository Retrieve Search Search all fields Folder Type Author Modified JTestiClemTest SPS admin Oct 20 2009 4 4 TestiClemTest SPS admin Oct 20 2009 5 3 Restrict search i sTestiClemTest SPS admin Oct 20 2009 5 3 T Title E TestiClemTest SPS admin Oct 20 2009 5 2 E Label modelingintro str Test SPS admin Sep 7 2009 3 27 modelingintro str Test SPS admin Sep 7 2009 3 27 iol Dota modelingintro str Test SPS admin Sep 7 2009 3 19 Documents created or modified madelingintro str Test SPS admin Sep 7 2009120 onor ater modelingintro str Test SPS admin Sep 7 2009 11 5 modelingintro str Test SPS admin Sep 7 2009 11 5 bayes_bankloan dobhupi SPS admin Jul 30 2009 2 08 Stream2 str i SPS admin dun 23 2009 2 2 act modelingintro str 7 SPS admin May 28 2009 10 Indexed Content modelingintro str lt SPS admin May 27 2009 5 F Description LabManagerETL LabManagerRe SPS admin Apr 21 2009 10 ClearQuestUnas DataCollection SPS admin Mar 16 2009 12 ClearQuestUnas DataCollection SPS admin Mar 12 2009 2 2 Contains ANY of the terms ClearQuestUnas DataCollection SPS admin Mar 12 2009 2 1 Must contain ALL of the terms ClearQuestUnas DataCollection SPS admin Mar 12 2009 1 5 ClearQuestUnas DataCollection SPS admin Mar 4 2009 7 09 ClearQuestUnas DataCollection SPS
206. i Enable parallel processing M Generate SQL IM Database Caching I Use relaxed conversion Note Whether SQL pushback and optimization are supported depends on the type of database in use For the latest information on which databases and ODBC drivers are supported and tested for use with IBM SPSS Modeler 15 see the corporate Support site at hitp www ibm com support Enable stream rewriting Select this option to enable stream rewriting in SPSS Modeler Two types of rewriting are available and you can select one or both Stream rewriting reorders the nodes in a stream behind the scenes for more efficient operation without altering stream semantics Optimize SOL generation This option enables nodes to be reordered within the stream so that more operations can be pushed back using SQL generation for execution in the database When it finds a node that cannot be rendered into SQL the optimizer will look ahead to see if there are any downstream nodes that can be rendered into SQL and safely moved in front of the problem node without affecting the stream semantics Not only can the database perform operations more efficiently than SPSS Modeler but such pushbacks act to reduce the size of the data set that is returned to SPSS Modeler for processing This in turn can 62 Chapter 5 reduce network traffic and speed stream operations Note that the Generate SQL check box must be selected for SQL optimization to have
207. ications of data mining techniques include the following Direct mail Determine which demographic groups have the highest response rate Use this information to maximize the response to future mailings Credit scoring Use an individual s credit history to make credit decisions Human resources Understand past hiring practices and create decision rules to streamline the hiring process Medical research Create decision rules that suggest appropriate procedures based on medical evidence Market analysis Determine which variables such as geography price and customer characteristics are associated with sales Quality control Analyze data from product manufacturing and identify variables determining product defects Policy studies Use survey data to formulate policy by applying decision rules to select the most important variables Health care User surveys and clinical data can be combined to discover variables that contribute to health Terminology The terms attribute field and variable refer to a single data item common to all cases under consideration A collection of attribute values that refers to a specific case is called a record an example or a case Assessing the Data Data mining is not likely to be fruitful unless the data you want to use meets certain criteria The following sections present some of the aspects of the data and its application that you should consider Ensure that the data is available
208. ick a selected comment and click Disconnect on its menu To delete a comment Select one or more comments to be deleted Do one of the following m Press the Delete key m Right click a selected comment and click Delete on its menu If the comment was attached to a node or nugget the connection line is deleted as well 84 Chapter 5 gt If the comment was originally a stream or SuperNode annotation that had been converted to a freestanding comment the comment is deleted from the canvas but its text is retained on the Annotations tab for the stream or SuperNode To show or hide comments for a stream Do one of the following m On the main menu click View gt Comments m Click the Show hide comments button in the toolbar Listing Stream Comments You can view a list of all the comments that have been made for a particular stream or SuperNode On this list you can m Change the order of comments m Edit the comment text m Change the foreground or background color of a comment Listing Comments To list the comments made for a stream do one of the following m On the main menu click Tools gt Stream Properties gt Comments m Right click a stream in the managers pane and click Stream Properties then Comments m Right click a stream background on the canvas and click Stream Properties then Comments 85 Building Streams Figure 5 39 Listing comments for a stream This is the source data
209. ied link function and so that the observations can be correlated Generalized linear mixed models cover a wide variety of models from simple linear regression to complex multilevel models for non normal longitudinal data The Cox regression node enables you to build a survival model for time to event data in the presence of censored records The model produces a survival function that predicts the probability that the event of interest has occurred at a given time f for given values of the input variables The Support Vector Machine SVM node enables you to classify data into one of two groups without overfitting SVM works well with wide data sets such as those with a very large number of input fields The Bayesian Network node enables you to build a probability model by combining observed and recorded evidence with real world knowledge to establish the likelihood of occurrences The node focuses on Tree Augmented Naive Bayes TAN and Markov Blanket networks that are primarily used for classification 37 Understanding Data Mining A The Self Learning Response Model SLRM node enables you to build a model in n which a single new case or small number of new cases can be used to reestimate the w model without having to retrain the model using all data A The Time Series node estimates exponential smoothing univariate Autoregressive Integrated Moving Average ARIMA and multivariate ARIMA or transfer function hay mode
210. ile node 244 Appendix A Vv v v v y vyv v v y Spacebar Selects the Variable File node Ctrl Enter Adds the Variable File node to the stream canvas This key combination also keeps selection on the Variable File node so that the next node added will be connected to it Tab Moves focus back to the node palette Right Arrow 4 times Moves to the Derive node Spacebar Selects the Derive node Alt Enter Adds the Derive node to the canvas and moves selection to the Derive node This node is now ready to be connected to the next added node Tab Moves focus back to the node palette Right Arrow 5 times Moves focus to the Histogram node in the palette Spacebar Selects the Histogram node Enter Adds the node to the stream and moves focus to the stream canvas Continue with the next example or save the stream if you want to try the next example at a later time Shortcut Keys Example Editing Nodes In this example you will use the stream built in the earlier example The stream consists of a Variable File node a Derive node and a Histogram node The instructions begin with focus on the third node in the stream the Histogram node Ctrl Left Arrow 2 times Moves focus back to the Variable File node Enter Opens the Variable File dialog box Tab through to the File field and type a text file path and name to select that file Press Ctrl Tab to navigate to the lower part of the dialog box tab through to the OK but
211. in scripting or parameter settings 119 Building CLEM Expressions Accessing the Expression Builder The Expression Builder is available in all nodes where CLEM expressions are used including Select Balance Derive Filler Analysis Report and Table nodes You can open it by clicking the calculator button just to the right of the formula field Figure 7 6 A variety of nodes with Expression Builder button fal Tempi han Ey wi a laln Derive as Conditional Mode Single 8 Multiple Discard Initial X E Time 0 or Outcome OFFSET Outcome 1 Condition AVE Tempinc 5 C em Ca Cae Creating Expressions The Expression Builder provides not only complete lists of fields functions and operators but also access to data values if your data is instantiated To Create an Expression Using the Expression Builder gt Type in the expression field using the function and field lists as references or gt Select the required fields and functions from the scrolling lists 120 Chapter 7 gt Double click or click the yellow arrow button to add the field or function to the expression field gt Use the operand buttons in the center of the dialog box to insert the operations into the expression Selecting Functions The function list displays all available CLEM functions and operators Scroll to select a function from the list or for easier searching use
212. in the window click Project on the View menu Setting the Default Project Phase gt gt Objects added to a project are added to a default phase of CRISP DM This means that you need to organize objects manually according to the data mining phase in which you used them It is wise to set the default folder to the phase in which you are currently working To select which phase to use as your default In CRISP DM view right click the folder for the phase to set as the default On the menu click Set as Default The default folder is displayed in bold type 202 Chapter 11 Classes View The Classes view in the project pane organizes your work in IBM SPSS Modeler categorically by the types of objects created Saved objects can be added to any of the following categories E Streams m Nodes m Models m Tables graphs reports m Other non SPSS Modeler files such as slide shows or white papers relevant to your data mining work Figure 11 3 Classes view aman om a unsaved project ables Graphs amp Reports a Patient Records 8 fields 200 records i Distribution of Drug i al Other Adding objects to the Classes view also adds them to the default phase folder in the CRISP DM view Note If the project pane is not visible in the window click Project on the View menu Building a Project A project is essentially a file containing references to all of the files that you associate with the project
213. information see the topic Values and Data Types in Chapter 7 on p 10 Additionally these rules are covered in more detail in the following topics Integers Integers are represented as a sequence of decimal digits Optionally you can place a minus sign before the integer to denote a negative number for example 1234 999 77 The CLEM language handles integers of arbitrary precision The maximum integer size depends on your platform If the values are too large to be displayed in an integer field changing the field type to Real usually restores the value Reals Real refers to a floating point number Reals are represented by one or more digits followed by a decimal point followed by one or more digits CLEM reals are held in double precision Optionally you can place a minus sign before the real to denote a negative number for example 1 234 0 999 77 001 Use the form lt number gt e lt exponent gt to express a real number in exponential notation for example 1234 0e5 1 7e 2 When the IBM SPSS Modeler application reads number strings from files and converts them automatically to numbers numbers with no leading digit before the decimal point or with no digit after the point are accepted for example 999 or 11 However these forms are illegal in CLEM expressions Note When referencing real numbers in CLEM expressions a period must be used as the decimal separator regardless of any sett
214. ing The simplest way to form a stream is to double click nodes on the palette This method automatically connects the new node to the selected node on the stream canvas For example if the canvas contains a Database node you can select this node and then double click the next node from the palette such as a Derive node This action automatically connects the Derive node to the existing Database node You can repeat this process until you have reached a terminal node such as a Histogram or Table node at which point any new nodes will be connected to the last non terminal node upstream 44 Chapter 5 Figure 5 2 Stream created by double clicking nodes from the palettes A Database Derive Filter To Connect Nodes Using the Middle Mouse Button On the stream canvas you can click and drag from one node to another using the middle mouse button If your mouse does not have a middle button you can simulate this by pressing the Alt key while dragging with the mouse from one node to another Figure 5 3 Using the middle mouse button to connect nodes Database Derive S0 To Manually Connect Nodes If you do not have a middle mouse button and prefer to manually connect nodes you can use the pop up menu for a node to connect it to another node already on the canvas gt Right click the node from which you want to start the connection Doing so opens the node menu gt On the menu click Connect g
215. ing Expressions 0 0 ccc cette teen teen teens SELECTING FUNCTIONS ice ie srne ea hee SG Paani ay hee sola a E E Oke ane ed Selecting Fields Parameters and Global Variables 0 0 0 c cece eee eee eee Viewing or Selecting Values 0 0 ccc ccc cen teen ene ene nee Checking CLEM Expressions 00s cece cece eet ete e etna Find and Replace 0 ccc een eee een Ea en tent e eens 8 CLEM Language Reference 127 CLEM OPGratorss senep orperetadt ddiet beter aik Anane teks dyeawle head ohaawe s Functions Reference 0 0 0c ccc eee eee ee eee eee eee eens Conventions in Function Descriptions 0 0 0 ccc cece ete teens Information Functions 1 1 eet ee een tenes Conversion Functions 00 0 nnana aeaaeae Comparison Functions 0 0 0 0 ccc eee teen tenet e eens vi Logical Functions sa 0 0 0 c ccc eee teen ene n eee nee Numeric Functions sisia hee hi ve ede Pe tw kG ee ae sie a E ew nee ea Trigonometric FUNCTIONS 0 0 cee etn e nen eens Probability Functions 0 0 0 cc cece ete nen tenes Bitwise Integer Operations 0 cent eet n eee Random Functions 0000s ccc cnt nee eee String FUNCHONS 5 3 50 dx chee ea ada wet dae wait wn Wieden en dated da et alee cena SoundEx Functions 0 000 tata nA inaa Daa a a OAT a E ee Date and Time Functions n nnana auaa Sequence Functions o orcireseirin sdb nr E ENTER ERCE RE Ea a E AA Global Functi
216. ing is useful for mapping to terminal nodes and copying and pasting between streams Note Using the Map to option you cannot map to Merge Append and all types of source nodes Figure 5 47 Mapping a stream from its Sort node to the Type node of another stream DRUG4n DRUG2n Na_to_K Discard Fields Define Types To Map Data between Streams Right click the node that you want to use for connecting to the new stream On the menu click Data Mapping gt Map to Use the cursor to select a destination node on the target stream In the dialog box that opens ensure that fields are properly matched and click OK Specifying Essential Fields When mapping to an existing stream essential fields will typically be specified by the stream author These essential fields indicate whether a particular field is used in downstream operations For example the existing stream may build a model that uses a field called Churn In this stream Churn is an essential field because you could not build the model without it Likewise fields used in manipulation nodes such as a Derive node are necessary to derive the new field Explicitly setting such fields as essential helps to ensure that the proper fields in the new source node are mapped to them If mandatory fields are not mapped you will receive an error message If you decide that certain manipulations or output nodes are unnecessary you can delete the nodes from the stream and remove t
217. ing new windows for generated Click Default Values to revert to the system default settings for this tab Using the Display tab of the User Options dialog box you can set options for the display of fonts and colors in IBM SPSS Modeler J User Options X Show welcome dialog on startup IM Show stream and SuperNode markups Standard Fonts amp Colors effective on restart Look and Feel Default font size for nodes Custom Colors SuperNode background color Flash color Link color Executing link color Non executing link color Link error color Comment background color Comment foreground color Chart Category Color Order Show welcome dialog on startup Select to cause the welcome dialog box to be displayed on startup The welcome dialog box has options to launch the application examples tutorial open a demonstration stream or an existing stream or project or to create a new stream Show stream and SuperNode markups If selected causes markup if any on streams and SuperNodes to be displayed by default Markup includes stream comments model links and scoring branch highlighting 221 Customizing IBM SPSS Modeler Standard Fonts amp Colors effective on restart Options in this control box are used to specify the SPSS Modeler screen design color scheme and the size of the fonts displayed Options selected here do not take effect until you close and restart SPSS Modeler
218. ing tab only for objects generated by the stream currently visible in the canvas m Select Never to restrict the software from switching to the corresponding tab to notify you of generated outputs or models Flash tab Select whether to flash the Outputs or Models tab in the managers pane when new outputs or models have been generated m Select If not selected to flash the corresponding tab if not already selected whenever new objects are generated in the managers pane m Select Never to restrict the software from flashing the corresponding tab to notify you of generated objects Scroll palette to make visible New Model only Select whether to automatically scroll the Models tab in the managers pane to make the most recent model visible m Select Always to enable scrolling m Select If generated by current stream to scroll only for objects generated by the stream currently visible in the canvas m Select Never to restrict the software from automatically scrolling the Models tab Open window New Output only Select whether to automatically open an output window upon generation 220 Chapter 12 Select Always to always open a new output window Select If generated by current stream to open a new window for output generated by the stream currently visible in the canvas output Setting Display Options Figure 12 3 User Options dialog box Display tab Select Never to restrict the software from automatically open
219. ing the Demos folder from the list of recently used directories T a a Look In Accessibility bin config Demos File Name Files of Type Minimize output window clutter You can close and delete output quickly using the red X button at the top right corner of all output windows This enables you to keep only promising or interesting results on the Outputs tab of the managers pane A full range of keyboard shortcuts is available for the software For more information see the topic Keyboard Accessibility in Appendix A on p 238 Did you know that you can m Drag and select a group of nodes on the stream canvas using your mouse m Copy and paste nodes from one stream to another m Access Help from every dialog box and output window E Get Help on CRISP DM the Cross Industry Standard Process for Data Mining On the Help menu click CRISP DM Help Chapter Handling Missing Values Overview of Missing Values During the Data Preparation phase of data mining you will often want to replace missing values in the data Missing values are values in the data set that are unknown uncollected or incorrectly entered Usually such values are invalid for their fields For example the field Sex should contain the values M and F If you discover the values Y or Z in the field you can safely assume that such values are invalid and should therefore be interpreted as blanks Likewise a negative value fo
220. ings for the current stream or locale For example specify Na gt 0 6 rather than Na gt 0 6 This applies even if a comma is selected as the decimal symbol in the stream properties dialog box and is consistent with the general guideline that code syntax should be independent of any specific locale or convention Characters Characters usually shown as CHAR are typically used within a CLEM expression to perform tests on strings For example you can use the function isuppercode to determine whether the first character of a string is upper case The following CLEM expression uses a character to indicate that the test should be performed on the first character of the string isuppercode subscrs 1 MyString To express the code in contrast to the location of a particular character in a CLEM expression use single backquotes of the form lt character gt for example A Z Note There is no CHAR storage type for a field so if a field is derived or filled with an expression that results in a CHAR then that result will be converted to a string 129 Strings Lists Fields Dates CLEM Language Reference Generally you should enclose strings in double quotation marks Examples of strings are c35product2 and referrerlD To indicate special characters in a string use a backslash for example 65443 To indicate a backslash character use a double backslash You can use single quotes around a string bu
221. into projects There are two tabs in this area reflecting two different views of a project The Classes view sorts project objects by type while the CRISP DM view sorts objects by the relevant data mining phase such as Data Preparation or Modeling These various aspects of the SPSS Modeler window are discussed throughout the Help system and User s Guide Following is a table of shortcuts used to move within the main SPSS Modeler window and build streams Shortcuts for dialog boxes and output are listed in the topics that follow Note that these shortcut keys are available only from the main window Main Window Shortcuts Shortcut Key Function Ctrl F5 Moves focus to the node palettes 239 Accessibility in IBM SPSS Modeler Shortcut Key Function Ctrl F6 Moves focus to the stream canvas Ctrl F7 Moves focus to the managers pane Ctrl F8 Moves focus to the project pane Node and Stream Shortcuts Shortcut Key Function Ctrl N Creates a new blank stream canvas Ctrl1 O Displays the Open dialog box from where you can select and open an existing stream Ctrl number keys Moves focus to the corresponding tab on a window or pane For example within a tabbed pane or window Ctrl 1 moves to the first tab starting from the left Ctrl 2 to the second etc Ctrl Down Arrow Used in the node palette to move focus from a palette tab to the first node under that tab
222. is is useful when you are managing the entire data mining process within SPSS Modeler For example you can store links to data notes presentations and graphics in a project In CRISP DM view external files can be added to the folder of your choice In Classes view external files can be saved only to the Other folder To add external files to a project Drag files from the desktop to the project or Right click the target folder in CRISP DM or Classes view On the menu click Add to Folder Select a file in the dialog box and click Open This will add a reference to the selected object inside SPSS Modeler projects Transferring Projects to the IBM SPSS Collaboration and Deployment Services Repository You can transfer an entire project including all component files to the IBM SPSS Collaboration and Deployment Services Repository in one step Any objects that are already in the target location will not be moved This feature also works in reverse you can transfer entire projects from the IBM SPSS Collaboration and Deployment Services Repository to your local file system Note A separate license is required to access an IBM SPSS Collaboration and Deployment Services repository For more information see hittp www ibm com software analytics spss products deployment cds 205 Projects and Reports Transferring a Project Make sure that the project you want to transfer is open in the project pane To transfer
223. is legal For example length Label gt 6 and Label 6 x This operation is a logical inclusive disjunction and returns a true value if either COND or COND2 is true or if both are true If COND is true COND2 is not evaluated COND1 and COND2 Boolean COND1 or COND2 Boolean This operation is a logical negation and returns a true not COND Boolean value if COND is false Otherwise this operation returns a value of 0 This operation is a conditional evaluation If COND if COND then EXPRI else Any is true this operation returns the result of EXPR EXPR2 endif Otherwise the result of evaluating EXPR2 is returned This operation is a multibranch conditional evaluation if COND1 then EXPR1 elseif If COND is true this operation returns the result of COND2 then EXPR2 else Any EXPRI1 Otherwise if COND2 is true this operation EXPR_N endif returns the result of evaluating EXPR2 Otherwise the result of evaluating EXPR_N is returned 138 Chapter 8 Numeric Functions CLEM contains a number of commonly used numeric functions Function Result Description _NUM Number Used to negate NUM Returns the corresponding number with the opposite sign NUM1 NUM2 Number Returns the sum of NUMI and NUM2 code NUM2 Number Returns the value of NUM2 subtracted from NUM1 NUM1 NUM2 Number Returns the value of NUM1 multiplied by NUM2 NUM1 NUM2 Number Returns the value
224. istribution and the observations can be correlated Generalized linear mixed models cover a wide variety of models from simple linear regression to complex multilevel models for non normal longitudinal data For more information see the topic New odes in This Release on p 0 Support for maps in the Graphboard node The Graphboard node now includes support for a large number of map types These include choropleths where regions can be given different colors or patterns to indicate different values and point overlay maps where geospatial points are overlaid on the map IBM SPSS Modeler ships with several map files but you can use the Map Conversion Utility to convert your existing map shapefiles for use with the Graphboard Template Chooser Netezza Time Series and Generalized Linear nodes Two new nodes are available for IBM Netezza Analytics in database mining Time Series and Generalized Linear For more information see the topic New Nodes in This Release on p 10 Netezza nodes enabled through Helper Applications The Netezza Analytics database modeling nodes are now enabled in the same way as the other database modeling nodes Zooming in and out on the stream view It is now possible to scale the entire stream view up or down from the standard size This feature is particularly useful for gaining an overall view of a complex stream or for minimizing the number of pages needed
225. ive years count_greater_than 5 cardtenure card2tenure card3tenure To count null values across the same set of fields count_nulls cardtenure card2tenure card3tenure Note that this example counts the number of cards being held not the number of people holding them For more information see the topic Comparison Functions in Chapter 8 on p 135 To count the number of times a specified value occurs across multiple fields you can use the count_equal function The following example counts the number of fields in the list that contain the value Y count_equal Y Answer1 Answer2 Answer3 Given the following values for the fields in the list the function returns the results for the value Y as shown Answerl Answer2 Answer3 Count Y N Y 2 Y N N 1 Numeric Functions You can obtain statistics across multiple fields using the sum_n mean_n and sdev_n functions for example sum_n card1bal card2bal card3bal mean_n card1bal card2bal card3bal For more information see the topic Numeric Functions in Chapter 8 on p 138 Generating Lists of Fields When using any of the functions that accept a list of fields as input the special functions FIELDS_BETWEEN start end and FIELDS_MATCHING pattern can be used as input For example assuming the order of fields is as shown in the sum_n example earlier the following would be eq
226. lable from the Output nodes palette is an indispensable tool for data understanding Data preparation After cataloging your data resources you will need to prepare your data for mining Preparations include selecting cleaning constructing integrating and formatting data m Modeling This is of course the flashy part of data mining where sophisticated analysis methods are used to extract information from the data This phase involves selecting modeling techniques generating test designs and building and assessing models m Evaluation Once you have chosen your models you are ready to evaluate how the data mining results can help you to achieve your business objectives Elements of this phase include evaluating results reviewing the data mining process and determining the next steps Deployment Now that you have invested all of this effort it is time to reap the benefits This phase focuses on integrating your new knowledge into your everyday business processes to solve your original business problem This phase includes plan deployment monitoring and maintenance producing a final report and reviewing the project There are some key points in this process model First while there is a general tendency for the process to flow through the steps in the order outlined in the previous paragraphs there are also a number of places where the phases influence each other in a nonlinear way For example data preparation usually precede
227. lette where available For more information see the topic Creating a Subpalette on p 227 229 Customizing IBM SPSS Modeler To change the nodes shown on a palette tab select the palette tab and then from the menu on the left select to display either all nodes or just those in a specific subpalette Figure 12 11 Modeling palette tab showing the Classification subpalette A OAA Decision List Linear Regression PCA Factor Neural Net eeee Feature Selection Discriminant Logistic GenLin CEMI Node Management CEMI is now deprecated and has been replaced by CLEF which offers a much more flexible and easy to use feature set For more information see the JBM SPSS Modeler 15 CLEF Developer s Guide supplied with this release Chapter 13 Performance Considerations for Streams and Nodes You can design your streams to maximize performance by arranging the nodes in the most efficient configuration by enabling node caches when appropriate and by paying attention to other considerations as detailed in this section Aside from the considerations discussed here additional and more substantial performance improvements can typically be gained by making effective use of your database particularly through SQL optimization Order of Nodes Even when you are not using SQL optimization the order of nodes in a stream can affect performance The general goal is to minimize downst
228. list of special keyboard and screen reader shortcuts follows Dialog Box and Expression Builder Shortcuts Shortcut Key Function Alt 4 Used to dismiss all open dialog boxes or output windows Output can be retrieved from the Outputs tab in the managers pane 241 Accessibility in IBM SPSS Modeler Shortcut Key Function Ctrl End With focus on any control in the Expression Builder this will move the insertion point to the end of the expression Ctrl 1 In the Expression Builder moves focus to the expression edit control Ctrl 2 In the Expression Builder moves focus to the function list Ctrl 3 In the Expression Builder moves focus to the field list Table Shortcuts Table shortcuts are used for output tables as well as table controls in dialog boxes for nodes such as Type Filter and Merge Typically you will use the Tab key to move between table cells and Ctrl Tab to leave the table control Note Occasionally a screen reader may not immediately begin reading the contents of a cell Pressing the arrow keys once or twice will reset the software and start the speech Shortcut Key Function Ctrl W For tables reads the short description of the selected roW For example Selected row 2 values are sex flag m f etc Ctrl Alt W For tables reads the long description of the selected roW For example Selected row 2
229. ll palette to make visible Always If generated by current stream O Never Calea azo _ geset petaut vanes Nodes added lt Show stream execution feedback dialog Select to display a dialog box that includes a progress indicator when a stream has been running for three seconds The dialog box also includes details of the output objects created by the stream m Close dialog upon completion By default the dialog box closes when the stream finishes running Clear this check box if you want the dialog box to remain visible when the stream finishes Warn when a node overwrites a file Select to warn with an error message when node operations overwrite an existing file Warn when a node overwrites a database table Select to warn with an error message when node operations overwrite an existing database table Sound Notifications Use the list to specify whether sounds notify you when an event or error occurs There are a number of sounds available Use the Play loudspeaker button to play a selected sound Use the ellipsis button to browse for and select a sound Note The wav files used to create sounds in SPSS Modeler are stored in the media sounds directory of your installation Mute all sounds Select to turn off sound notification for all events 219 Customizing IBM SPSS Modeler Visual Notifications The options in this group are used to specify the behavior of the O
230. ll related job steps This means that you no longer have to change the job steps one by one Choice of execution branch in deployed streams For stream job steps in IBM SPSS Collaboration and Deployment Services if the stream contains branches you can now choose one or more stream branches to execute 10 Chapter 2 New features in IBM SPSS Modeler Premium IBM SPSS Modeler Premium is a separately licensed product that provides additional features to those supplied by IBM SPSS Modeler Professional Previously SPSS Modeler Premium included only IBM SPSS Modeler Text Analytics The full set of SPSS Modeler Premium features is now as follows m SPSS Modeler Text Analytics IBM SPSS Modeler Entity Analytics IBM SPSS Modeler Social Network Analysis SPSS Modeler Text Analytics uses advanced linguistic technologies and Natural Language Processing NLP to rapidly process a large variety of unstructured text data extract and organize the key concepts and group these concepts into categories Extracted concepts and categories can be combined with existing structured data such as demographics and applied to modeling using the full suite of IBM SPSS Modeler data mining tools to yield better and more focused decisions IBM SPSS Modeler Entity Analytics adds a completely new dimension to SPSS Modeler predictive analytics Whereas predictive analytics attempts to predict future behavior from past data entity analytic
231. log Display SOL generation details in the messages log during stream preparation During stream preview specifies whether a preview of the SQL that would be generated is passed to the messages log Display SOL Specifies whether any SQL that is displayed in the log should contain native SQL functions or standard ODBC functions of the form fn FUNC as generated by IBM SPSS Modeler The former relies on ODBC driver functionality that may not be implemented For example this control would have no effect for SQL Server 64 Chapter 5 Reformat SOL for improved readability Specifies whether SQL displayed in the log should be formatted for readability Show status for records Specifies when records should be reported as they arrive at terminal nodes Specify a number that is used for updating the status every N records Save As Default The options specified apply only to the current stream Click this button to set these options as the default for all streams Setting layout options for streams These settings provide a number of options relating to the display and use of the stream canvas Figure 5 21 Setting display layout options for a stream OStreamt i B Select a setting These settings control display features of the stream canvas for the current stream Click Save As Default to use Senarai these settings as the default for all your streams Date Time Number formats Minimum Stream canvas width 1680
232. ls for time series data and produces forecasts of future performance A Time Series node must always be preceded by a Time Intervals node A The k Nearest Neighbor KNN node associates a new case with the category or value se of the k objects nearest to it in the predictor space where k is an integer Similar cases E3 are near each other and dissimilar cases are distant from each other Association Models Association models find patterns in your data where one or more entities such as events purchases or attributes are associated with one or more other entities The models construct rule sets that define these relationships Here the fields within the data can act as both inputs and targets You could find these associations manually but association rule algorithms do so much more quickly and can explore more complex patterns Apriori and Carma models are examples of the use of such algorithms One other type of association model is a sequence detection model which finds sequential patterns in time structured data Association models are most useful when predicting multiple outcomes for example customers who bought product X also bought Y and Z Association models associate a particular conclusion such as the decision to buy something with a set of conditions The advantage of association rule algorithms over the more standard decision tree algorithms C5 0 and C amp RT is that associations can exist between any of the attributes
233. lues are blank according to the blank handling rules set in an upstream Type node or source node Types tab Note that this function cannot be called from a script LAST_NON_BLANK FIELD Any Returns the last value for FIELD that was not blank as defined in an upstream source or Type node If there are no nonblank values for FIELD in the records read so far null is returned Note that blank values also called user missing values can be defined separately for each field NULL FIELD Boolean Returns true if the value of FIELD is the system missing null Returns false for all other values including user defined blanks If you want to check for both use BLANK FIELD and NULL FIELD undef Any Used generally in CLEM to enter a null value for example to fill blank values with nulls in the Filler node Blank fields may be filled in with the Filler node In both Filler and Derive nodes multiple mode only the special CLEM function FIELD refers to the current field s being examined 157 CLEM Language Reference Special Fields Special functions are used to denote the specific fields under examination or to generate a list of fields as input For example when deriving multiple fields at once you should use FIELD to denote perform this derive action on the selected fields Using the expression log FIELD derives a new log field for each selected field Note
234. ly defined process model for data mining The process model helps you answer the questions listed earlier in this section and makes sure the important points are addressed It serves as a data mining road map so that you will not lose your way as you dig into the complexities of your data The data mining process suggested for use with SPSS Modeler is the Cross Industry Standard Process for Data Mining CRISP DM As you can tell from the name this model is designed as a general model that can be applied to a wide variety of industries and business problems The CRISP DM Process Model The general CRISP DM process model includes six phases that address the main issues in data mining The six phases fit together in a cyclical process designed to incorporate data mining into your larger business practices 33 Understanding Data Mining Figure 4 1 CRISP DM process model The six phases include m Business understanding This is perhaps the most important phase of data mining Business understanding includes determining business objectives assessing the situation determining data mining goals and producing a project plan m Data understanding Data provides the raw materials of data mining This phase addresses the need to understand what your data resources are and the characteristics of those resources It includes collecting initial data describing data exploring data and verifying data quality The Data Audit node avai
235. main menu click File gt Project gt Store Project 171 Using IBM SPSS Modeler with a Repository gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p 161 For specific port password and other connection details contact your local system administrator gt In the Repository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 1641 Storing Nodes You can store an individual node definition from the current stream as a nod file in the repository from where it can be accessed by other users To store a node gt Right click the node in the stream canvas and click Store Node gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator gt Inthe Repository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 164 Storing Output Objects You can store an outp
236. me Series node and the Time Plot graph node are available together from a unique palette tab The Palette Manager enables you to easily make these adjustments by creating your custom palette tabs in the Nodes Palette The Palette Manager enables you to carry out various tasks Control which palette tabs are shown on the Nodes Palette below the stream canvas Change the order in which palette tabs are shown on the Nodes Palette Create and edit your own palette tabs and any associated subpalettes Edit the default node selections on your Favorites tab To access the Palette Manager gt On the Tools menu click Manage Palettes 224 Chapter 12 Figure 12 6 Palette Manager showing the tabs displayed on the Nodes Palette Palette Manager Palettes can be created and edited here User defined palettes To create edit sub palettes choose a palette and select the sub palettes button No of nodes Shown 16 9 9 17 9 29 Palette Name Each available palette tab whether shown on the Nodes Palette or not is listed This includes any palette tabs that you have created For more information see the topic Creating a Palette Tab on p 225 No of nodes The number of nodes displayed on each palette tab A high number here means you may find it more convenient to create subpalettes to divide up the nodes on the tab For more v Ei Ej v Ei Ti v A information see
237. me and port number This information is automatically provided However you still need the correct logon information such as username domain and password Note If you do not have access to the Coordinator of Processes capability you can still manually enter the server name to which you want to connect or select a name that you have previously defined For more information see the topic Adding and Editing the IBM SPSS Modeler Server Connection on p 14 Figure 3 4 Search for Servers dialog box Search for Servers Servers found Server Name Description Mktg Tester 778 Mkt Test Servers Mktg Prod 778 Marketing Dept Producti To search for servers and clusters gt On the Tools menu click Server Login The Server Login dialog box opens In this dialog box click Search to open the Search for Servers dialog box If you are not logged on to IBM SPSS Collaboration and Deployment Services when you attempt to browse the Coordinator of Processes you will be prompted to do so For more information see the topic Connecting to the Repository in Chapter 9 on p 61 gt Select the server or server cluster from the list gt Click OK to close the dialog box and add this connection to the table in the Server Login dialog box Changing the Temp Directory Some operations performed by IBM SPSS Modeler Server may require temporary files to be create
238. me when the version was stored Label Current label for the version if any Unlike the version identifier labels can be moved from one version of an object to another The file size creation date and author are also displayed for each version Edit Labels Click the Edit Labels icon at the top right of the Versions tab to define apply or remove labels for stored objects For more information see the topic Managing Object Version Labels on p 183 Permissions Tab The Permissions tab lets you set read and write permissions for the object All users and groups with access to the current object are listed Permissions follow a hierarchy For example if you do not have read permission you cannot have write permission If you do not have write permission you cannot have delete permission 183 Using IBM SPSS Modeler with a Repository Figure 9 22 Object access rights Repository Object Properties Users And Groups everyone Users And Groups Lists the repository users and groups that have at least Read access to this object Select the Write and Delete check boxes to add those access rights for this object to a particular user or group Click the Add Users Groups icon on the right side of the Permissions tab to assign access to additional users and groups The list of available users and groups is controlled by the administrator Managing Object Version Labels The Edit Version
239. menu Caching Nodes in a Database For streams run in a database data can be cached midstream to a temporary table in the database rather than the file system When combined with SQL optimization this may result in significant gains in performance For example the output from a stream that merges multiple tables to create a data mining view may be cached and reused as needed By automatically generating SQL for all downstream nodes performance can be further improved When using database caching with strings longer than 255 characters either ensure that there is a Type node upstream from the caching node and that the field values are read or set the string length by means of the default_sql_string_length parameter in the options cfg file Doing so ensures that the corresponding column in the temporary table is set to the correct width to accommodate the strings To take advantage of database caching both SQL optimization and database caching must be enabled Note that Server optimization settings override those on the Client For more information see the topic Setting optimization options for streams on p 60 With database caching enabled simply right click any nonterminal node to cache data at that point and the cache will be created automatically directly in the database the next time the stream is run If database caching or SQL optimization is not enabled the cache will be written to the file system instead 52
240. models generated using database native algorithms PMML export is available for IBM InfoSphere Warehouse models only Models created using Analysis Services from Microsoft or Oracle Data Miner cannot be exported Also note that IBM models exported as PMML cannot be imported back into SPSS Modeler PMML Import SPSS Modeler can import and score PMML models generated by current versions of all IBM SPSS Statistics products including models exported from SPSS Modeler as well as model or transformation PMML generated by SPSS Statistics 17 0 or later Essentially this means any PMML that the scoring engine can score with the following exceptions m Apriori CARMA Anomaly Detection and Sequence models cannot be imported m PMML models may not be browsed after importing into SPSS Modeler even though they can be used in scoring Note that this includes models that were exported from SPSS Modeler to begin with To avoid this limitation export the model as a generated model file gm rather than PMML IBM InfoSphere Warehouse models exported as PMML cannot be imported Limited validation occurs on import but full validation is performed on attempting to score the model Thus it is possible for import to succeed but scoring to fail or produce incorrect results Chapter Projects and Reports Introduction to Projects A project is a group of files related to a data mining task Projects include data streams graphs generated models
241. most cases and is required for Champion Challenger analysis m If Champion Challenger support is not required different Enterprise View connections can be used within the same branch as long as the connections vary by data provider definition DPD only m These limitations apply within a given branch only Between the scoring and model building branches different Enterprise View connections can be used without such restrictions 188 Chapter 9 Scoring and Modeling Parameters When deploying a stream to IBM SPSS Collaboration and Deployment Services you can choose which parameters can be viewed or edited each time the model is updated or scored For example you might specify maximum and minimum values or some other value that may be subject to change each time a job is run Figure 9 25 Scoring Parameters dialog box i Scoring Parameters Select which parameters you wish to allow users to see and edit for scoring Show Parameter Description Fi E MinYalue Minimum value Mo PP Maxvaue Maximum value gt To make a parameter visible so it can be viewed or edited after the stream is deployed select it from the list in the dialog box The list of available parameters is defined on the Parameters tab in the stream properties dialog box For more information see the topic Setting Stream and Session Parameters on p 68 The Scoring Branch in Chapter 5 If you are depl
242. moves to the next item on the list If a menu has focus moves to the next item on the menu If a thumbnail graph has focus moves to the next one in the set or to the first one if the last thumbnail has focus Up Arrow If a drop down list is open moves to the previous item on the list If a menu has focus moves to the previous item on the menu If a thumbnail graph has focus moves to the previous one in the set or to the last one if the first thumbnail has focus Enter Closes an open drop down list or makes a selection on an open menu F6 Toggles focus between the left and right hand panes of the window Left and Right Arrows If a tab has focus moves to the previous or next tab If a menu has focus moves to the previous or next menu Alt letter Selects the button or menu having this letter underlined in its name Esc Closes an open menu or drop down list 243 Accessibility in IBM SPSS Modeler Cluster Viewer only The Cluster Viewer has a Clusters view that contains a cluster by features grid To choose the Clusters view instead of the Model Summary view Press Tab repeatedly until the View button is selected Press Down Arrow twice to select Clusters From here you can select an individual cell within the grid Press Tab repeatedly until you arrive at the last icon in the visualization toolbar Figure A 1 Show Visualization Tree icon L Press Tab once more then Spacebar th
243. mp Comparison Used to compare field values to each other or to a specified string For example lt is used to compare whether the values of two fields are lesser or equal ogicall Used to perform logical operations such as if then else operations Used to perform numeric calculations such as the natural log of umeric field values Used to perform trigonometric calculations such as the arccosine Trigonometric s of a specified angle Return probabilities based on various distributions such as Probability probability that a value from Student s rf distribution will be less than a specific value Bitwise Used to manipulate integers as bit patterns andom Used to randomly select items or generate numbers String Used to perform a wide variety of operations on strings such as 8 stripchar which allows you to remove a specified character EE Sounda Used to find strings when the precise spelling is not known based on phonetic assumptions about how certain letters are pronounced Used to perform a variety of operations on date time and timestamp ate and time fields Sequence Used to gain insight into the record sequence of a data set or perform operations based on that sequence Global Used to access global values created by a Set Globals node For example MEAN is used to refer to the mean averag
244. ms in Chapter 5 on p 55 Function Result Description ITEM1 gt lt ITEM2 String Concatenates values for two fields and returns the resulting string as TTEM1ITEM2 to_integer ITEM Integer Converts the storage of the specified field to an integer to_real ITEM Real Converts the storage of the specified field to a real to_number ITEM Number Converts the storage of the specified field to a number to_string ITEM String Converts the storage of the specified field to a string to_time ITEM Time Converts the storage of the specified field to a time to_date ITEM Date Converts the storage of the specified field to a date to_timestamp ITEM Timestamp Converts the storage of the specified field to a timestamp to_datetime ITEM Datetime Converts the storage of the specified field to a date time or timestamp value Returns the date value for a number string or timestamp Note this is the only function that allows you to convert a number in seconds back to a date If ITEM is a string creates a date by parsing a string in the current date format The date format specified in the stream properties dialog datetime_date ITEM Date box must be correct for this function to be successful If ITEM is a number it is interpreted as a number of seconds since the base date or epoch Fractions of a day are truncated If ITEM is a timestamp the date part of the timestamp is returned If ITEM is a
245. n Dec 29 07 Administrator PES40Planning PlanningData lanningReports MDemo PMDemoData Information for selected version Name modelingintro str Version 1 2009 05 28 04 21 15 478 Labels none Created By admin Creation Date May 28 2009 Keywords Sl PredictiveAppsRe Extensive Versioning and Search Support The repository provides comprehensive object versioning and search capabilities For example suppose that you create a stream and store it in the repository where it can be shared with researchers from other divisions If you later update the stream in SPSS Modeler you can add the updated version to the repository without overwriting the previous version All versions remain accessible and can be searched by name label fields used or other attributes You could for example search for all model versions that use net revenue as an input or all models created by a particular author To do this with a traditional file system you would have to save each version under a different filename and the relationships between versions would be unknown to the software Single Sign On The single sign on feature enables users to connect to the repository without having to enter username and password details each time The user s existing local network login details provide the necessary authentication to IBM SPSS Collaboration and Deployment Services This feature depends on the following m IBM SPSS
246. n access to additional users and groups The list of available users and groups is controlled by the administrator Cascade Permissions Choose an option to control how changes made to the current folder are applied to its child folders if any m Cascade all permissions Cascades permission settings from the current folder to all child and descendant folders This is a quick way to set permissions for several folders at once Set permissions as required for the parent folder and then cascade as required m Cascade changes only Cascades only changes made since the last time changes were applied For example if a new group has been added and you want to give it access to all folders under the Sales branch you can give the group access to the root Sales folder and cascade the change to all subfolders All other permissions to existing subfolders remain as before m Donot cascade Any changes made apply to the current folder only and do not cascade to child folders Viewing and Editing Object Properties In the Object Properties dialog box you can view and edit properties Although some properties cannot be changed you can always update an object by adding a new version 181 Using IBM SPSS Modeler with a Repository gt In the repository window right click the required object gt Click Object Properties Figure 9 20 Object properties Repository Object Properties Name Created on Wed Sep 03 12 28 05 BST 2008 Last m
247. n complete Elapsed 0 05 sec CPU 0 0 sec A Execution was interrupted Failed to open create file C Program FilesYBM SPSSModeler 1 5 DemostsnapshottestN db If SQL optimization and logging options are enabled in the User Options dialog box then information on generated SQL is also displayed For more information see the topic Setting optimization options for streams on p 60 You can save messages reported here for a stream by clicking Save Messages on the Save button drop down list on the left just below the Messages tab You can also clear all messages for a given stream by clicking Clear All Messages on the Save button list Viewing Node Execution Times On the Messages tab you can also choose to display Execution Times where you can see the individual execution times for all the nodes in the stream Note For this feature to work the Display execution times check box must be selected on the General setting of the Options tab 68 Chapter 5 Figure 5 24 Viewing execution times for nodes in the stream mode lingintro xi E E Show General messages Execution time Terminal Node Node Label Node ID Execution Time s Credit rating id5QNPG99814T Analysis idTZPDFRJICS Credit rating idSQNPGS9SI4T Table idSFUQBGCL494 In the table of node execution times the columns are as follows Click a column heading to sort the entries into ascending or descending order
248. n the IBM SPSS Modeler15 shortcut the one with the icon right click and select Properties gt In the Target text box add noshare to the end of the string gt In Windows Explorer select Tools gt Folder Options gt On the File Types tab select the SPSS Modeler Stream option and click Advanced gt In the Edit File Type dialog box select Open with SPSS Modeler and click Edit gt In the Application used to perform action text box add noshare before the stream argument IBM SPSS Modeler Interface at a Glance At each point in the data mining process I BM SPSS Modeler s easy to use interface invites your specific business expertise Modeling algorithms such as prediction classification segmentation and association detection ensure powerful and accurate models Model results can easily be deployed and read into databases IBM SPSS Statistics and a wide variety of other applications Working with SPSS Modeler is a three step process of working with data m First you read data into SPSS Modeler m Next you run the data through a series of manipulations m Finally you send the data to a destination 18 Chapter 3 This sequence of operations is known as a data stream because the data flows record by record from the source through each manipulation and finally to the destination either a model or type of data output Figure 3 5 A simple stream gt _ Var File Derive
249. n with the specified degrees of freedom will be less than the specified number Returns the probability that a value from the F cdf_f NUM DF1 DF2 Real distribution with degrees of freedom DF and DF2 will be less than the specified number 140 Chapter 8 Function Result Description Returns the probability that a value from the normal os eer MEAN Real distribution with the specified mean and standard deviation will be less than the specified number Returns the probability that a value from Student s t cdf_t NUM DF Real distribution with the specified degrees of freedom will be less than the specified number Bitwise Integer Operations These functions enable integers to be manipulated as bit patterns representing two s complement values where bit position N has weight 2 N Bits are numbered from 0 upward These operations act as though the sign bit of an integer is extended indefinitely to the left Thus everywhere above its most significant bit a positive integer has 0 bits and a negative integer has 1 bit Note Bitwise functions cannot be called from scripts Function Result Description INT1 Integer Produces the bitwise complement of the integer JNT That is there is a 1 in the result for each bit position for which ZNT has 0 It is always true that INT INT 1 Note that this function cannot be called from a script INT1 INT2 Integ
250. nal node Note You can customize the Nodes palette For more information see the topic Customizing the Nodes Palette in Chapter 12 on p 223 Adding Nodes to a Stream There are several ways to add nodes to a stream from the nodes palette m Double click a node on the palette Note Double clicking a node automatically connects it to the current stream For more information see the topic Connecting Nodes in a Stream on p 43 Drag and drop a node from the palette to the stream canvas Click a node on the palette and then click the stream canvas Select an appropriate option from the Insert menu of IBM SPSS Modeler Once you have added a node to the stream canvas double click the node to display its dialog box The available options depend on the type of node that you are adding For information about specific controls within the dialog box click its Help button Removing Nodes To remove a node from the data stream click it and either press the Delete key or right click and select Delete from the menu Connecting Nodes in a Stream Nodes added to the stream canvas do not form a data stream until they have been connected Connections between the nodes indicate the direction of the data as it flows from one operation to the next There are a number of ways to connect nodes to form a stream double clicking using the middle mouse button or manually To Add and Connect Nodes by Double Click
251. ndReptace Find text myVariable v Replace with yourVariable a Options IM Match case E Whole words only E Regular expressions E Selected text only Ges mews eens Cree 0 With the cursor in a text area press Ctrl F to access the Find Replace dialog box Enter the text you want to search for or choose from the drop down list of recently searched items Enter the replacement text if any Click Find Next to start the search Click Replace to replace the current selection or Replace All to update all or selected instances The dialog box closes after each operation Press F3 from any text area to repeat the last find operation or press Ctrl F to access the dialog box again Search Options Match case Specifies whether the find operation is case sensitive for example whether myvar matches myVar Replacement text is always inserted exactly as entered regardless of this setting Whole words only Specifies whether the find operation matches text embedded within words If selected for example a search on spider will not match spiderman or spider man Regular expressions Specifies whether regular expression syntax is used see next section When selected the Whole words only option is disabled and its value is ignored Selected text only Controls the scope of the search when using the Replace All option Regular Expression Syntax Regular expressions allow you to search on special
252. ng A a amp GB Database Var File Auto Data Prep Select Sample Aggregate Derive ype Filter Graphboard Auto Classifier Auto Numeric Auto Cluster Table Flat File Dat Copyright IBM Corporation 1994 2012 12 13 IBM SPSS Modeler Overview Launching from the Command Line You can use the command line of your operating system to launch IBM SPSS Modeler as follows gt Onacomputer where IBM SPSS Modeler is installed open a DOS or command prompt window gt To launch the SPSS Modeler interface in interactive mode type the modelerclient command followed by the required arguments for example modelerclient stream report str execute The available arguments flags allow you to connect to a server load streams run scripts or specify other parameters as needed Connecting to IBM SPSS Modeler Server IBM SPSS Modeler can be run as a standalone application or as a client connected to IBM SPSS Modeler Server directly or to an SPSS Modeler Server or server cluster through the Coordinator of Processes plug in from IBM SPSS Collaboration and Deployment Services The current connection status is displayed at the bottom left of the SPSS Modeler window Whenever you want to connect to a server you can manually enter the server name to which you want to connect or select a name that you have previously defined However if you have IBM SPSS Collaboration and Depl
253. ng at source nodes which simply stores a copy of the original data as it is read into IBM SPSS Modeler will not improve performance in most circumstances Nodes with caching enabled are displayed with a small document icon at the top right corner When the data is cached at the node the document icon is green 232 Chapter 13 gt gt Figure 13 1 Caching at the Type node to store newly derived fields COND1n Pressure Warnings Templne Powerline PowerFlux PoweyState type to_number to_string Discard fields Discard Initial TempChange PowerChange Outcome Outcome To Enable a Cache On the stream canvas right click the node and click Cache on the menu On the caching submenu click Enable gt You can turn the cache off by right clicking the node and clicking Disable on the caching submenu Caching Nodes in a Database For streams run in a database data can be cached midstream to a temporary table in the database rather than the file system When combined with SQL optimization this may result in significant gains in performance For example the output from a stream that merges multiple tables to create a data mining view may be cached and reused as needed By automatically generating SQL for all downstream nodes performance can be further improved When using database caching with strings longer than 255 characters either ensure that there is a Type node upstream from t
254. nt Options The Deployment tab of the stream properties dialog box enables you to specify options for deploying the stream as a scenario within IBM SPSS Collaboration and Deployment Services for the purposes of model refresh automated job scheduling or further use by IBM 72 Chapter 5 Analytical Decision Management or Predictive Applications 5 x All streams require a designated scoring branch before they can be deployed additional requirements and options depend on the deployment type For more information see the topic in Chapter 9 on p 160 Viewing Global Values for Streams Storing and Deploying Repository Objects Using the Globals tab in the stream properties dialog box you can view the global values set for the current stream Global values are created using a Set Globals node to determine statistics such as mean sum or standard deviation for selected fields Once the Set Globals node is run these values are then available for a variety of uses in stream operations For more information see the topic Global Functions in Chapter 8 on p 155 To View Global Values for a Stream On the File menu click Stream Properties or select the stream from the Streams tab in the managers pane right click and then click Stream Properties on the pop up menu Click the Globals tab Alternatively on the Tools menu click Stream Properties gt Globals Figure 5 28 Viewing global
255. number string or timestamp Note this is the only function that allows you to convert a number in seconds back to a date If ITEM is a string creates a date by parsing a string in the current date format The date format specified in the stream properties dialog box must be correct for this function to be successful If ITEM is a number it is interpreted as a number of seconds since the base date or epoch Fractions of a day are truncated If ITEM is timestamp the date part of the timestamp is returned If ITEM is a date it is returned unchanged date_before DATE1 DATE2 Boolean Returns a value of true if DATE represents a date or timestamp before that represented by DATE2 Otherwise this function returns a value of 0 date_days_difference DATE1 DATE2 Integer Returns the time in days from the date or timestamp represented by DATE to that represented by DATE2 as an integer If DATE2 is before DATEJ this function returns a negative number date_in_days DATE Integer Returns the time in days from the baseline date to the date or timestamp represented by DATE as an integer If DATE is before the baseline date this function returns a negative number You must include a valid date for the calculation to work appropriately For example you should not specify 29 February 2001 as the date Because 2001 is a not a leap year this date does not exist date_in_months DATE Real Returns th
256. o which they are attached Nodes and nuggets can have more than one comment attached and the stream can have any number of freestanding comments Note You can also show stream annotations as on screen comments though these cannot be attached to nodes or nuggets For more information see the topic Converting Annotations to Comments on p 85 80 Chapter 5 The appearance of the text box changes to indicate the current mode of the comment or annotation shown as a comment as the following table shows Table 5 1 Comment and annotation text box modes Comment text box Annotation text Mode Indicates Obtained by box Edit Comment is open for Creating a new comment editing or annotation or double clicking an existing one Last Comment can be moved Clicking the stream i selectedresized or deleted background after editing or single clicking an existing comment or annotation View Editing is complete Clicking on another node comment or annotation after editing When you create a new freestanding comment it is initially displayed in the top left corner of the stream canvas Figure 5 35 New freestanding comment a NewsChan sav Type S NEWSCHAN If you are attaching a comment to a node or nugget the comment is initially displayed above the stream object to which it is attached Figure 5 36 New comment attached to node
257. ocus on the managers pane or project pane moves focus to the stream canvas With focus on a node palette moves focus between a node and its palette tab Any alphabetic key With focus on a node in the current stream gives focus and cycles to the next node whose name starts with the key pressed Fl Opens the Help system at a topic relevant to the focus F2 Starts the connection process for a node selected in the canvas Use the Tab key to move to the required node on the canvas and press Shift Spacebar to finish the connection F3 Deletes all connections for the selected node on the canvas F6 Moves focus between the managers pane project pane and node palettes F10 Opens the File menu Shift F10 Opens the pop up menu for the node or stream Delete Deletes a selected node from the canvas Esc Closes a pop up menu or dialog box Ctrl Alt X Expands a SuperNode Ctrl Alt Z Zooms in on a SuperNode Ctrl Alt Shift Z Zooms out of a SuperNode Ctrl E With focus in the stream canvas this runs the current stream A number of standard shortcut keys are also used in SPSS Modeler such as Ctrl C to copy For more information see the topic sing Shortcut Keys in Chapter 3 on p 26 Shortcuts for Dialog Boxes and Tables Several shortcut and screen reader keys are helpful when you are working with dialog boxes tables and tables in dialog boxes A complete
258. odified Wed Sep 03 12 28 09 BST 2008 Author Description Linked Topics Keywords General Tab Name The name of the object as viewed in the repository Created on Date the object not the version was created Last modified Date the most recent version was modified Author The user s login name Description By default this contains the description specified on the object s Annotation tab in SPSS Modeler Linked topics The repository allows models and related objects to be organized by topics if required The list of available topics is set by repository users with the appropriate privileges for more information see the Deployment Manager User s Guide Keywords You specify keywords on the Annotation tab for a stream model or output object Multiple keywords should be separated by spaces up to a maximum of 255 characters If keywords contain spaces use quotation marks to separate them Versions Tab Objects stored in the repository may have multiple versions The Versions tab displays information about each version 182 Chapter 9 Figure 9 21 Version properties a Repository Object Properties Labels Size Creation Date Created By Information for selected version Name Drug gm Wersion 0 2008 09 03 06 28 05 566 The following properties can be specified or modified for specific versions of a stored object Version Unique identifier for the version generated based on the ti
259. of NUM divided by NUM2 Used to perform integer division Returns the value of INTI INT1 div INT2 Number divided by INT2 S Returns the remainder of INT divided by INT2 For example ENE Number INT1 INT1 div INT2 INT2 INT1 mod INT Number This function has been deprecated Use the rem function instead Returns BASE raised to the power POWER where either may be any number except that BASE must not be zero if POWER is zero of any type other than integer 0 If POWER is an integer the computation is performed by successively BASE POWER Number multiplying powers of BASE Thus if BASE is an integer the result will be an integer If POWER is integer 0 the result is always a 1 of the same type as BASE Otherwise if POWER is not an integer the result is computed as exp POWER log BASE Returns the absolute value of NUM which is always a number abs NUM Number of the same type Returns e raised to the power NUM where e is the base of exp NUM Real natural logarithms Returns the fractional part of NUM defined as fracof NUM Real NUM intof NUM Truncates its argument to an integer It returns the integer of intof NUM Integer the same sign as NUM and with the largest magnitude such that abs INT lt abs NUM log NUM Real Returns the natural base e logarithm of NUM which must not be a zero of any kind Returns the base 10 logarithm of NUM which must not be log10 NUM Real
260. ollowing condition under Replace with replace FIELD m Deriving a flag field based on the presence of a specific substring For example you could use a string function in a Derive node to generate a separate flag field for each response with an expression such as hassubstring museums museum_of_design For more information see the topic String Functions in Chapter 8 on p 41 Handling Blanks and Missing Values Replacing blanks or missing values is a common data preparation task for data miners CLEM provides you with a number of tools to automate blank handling The Filler node is the most common place to work with blanks however the following functions can be used in any node that accepts CLEM expressions m BLANK FIELD can be used to determine records whose values are blank for a particular field such as Age m NULL FIELD can be used to determine records whose values are system missing for the specified field s In IBM SPSS Modeler system missing values are displayed as null values 114 Chapter 7 Figure 7 4 Filler node replacing system missing values with O For more information see the topic 156 on p Working with Numbers Filler Condition NULL FIELD i ha Replace with fF Cc ti Low cone spe Bese unctions Handling Blanks and Null Values in Chapter 8 Numerous standard operations on numeric
261. om spss Technical support Technical support is available to maintenance customers Customers may contact Technical Support for assistance in using IBM Corp products or for installation help for one of the supported hardware environments To reach Technical Support see the IBM Corp web site at fhittp www ibm com support Be prepared to identify yourself your organization and your support agreement when requesting assistance Copyright IBM Corporation 1994 2012 iii Contents 1 About IBM SPSS Modeler u IBM SPSS Modeler Products 0 ccc cece eee eect eee eee e eens 4 IBM SPSS Modeler 0 000 Aer aea a ae a e eee teens 4 IBM SPSS Modeler Server 0 0000 ccc ccc eee cee eee eee ees 2 IBM SPSS Modeler Administration Console nona 00 0 0 ccc cece eee eee 2 IBM SPSS Modeler Batch 0 0 0 0 ccc ccc tee tent e eee e i ia 2 IBM SPSS Modeler Solution Publisher 0 00 00 ccc a 2 IBM SPSS Modeler Server Adapters for IBM SPSS Collaboration and Deployment Services 2 IBM SPSS Modeler Editions 1 0 0 0 00000 c cee eee eee eens 3 IBM SPSS Modeler Documentation 000 000 cece eee eee eee 4 SPSS Modeler Professional Documentation 00 0000 ccc eee eee eee eee A SPSS Modeler Premium Documentation 0 0 00 ccc cece eee eee ee eee 5 Application Examples s iccacis lt cass vedw Pde dad iever dae eed eed bbw de ae bed 5 Demos Folder 0
262. on A Histogram To delete all connections to and from a node do one of the following m Select the node and press F3 m Select the node and on the main menu click Edit gt Node gt Disconnect Setting Options for Nodes Once you have created and connected nodes there are several options for customizing nodes Right click a node and select one of the menu options 49 Building Streams Figure 5 11 Pop up menu options for nodes DRUGIn i Connect Disconnect Rename and Annotate Ei New Comment Disable Node Cut Copy Node gt lt Delete Load Node FB Retrieve Node Save Node amp Store Node Cache Data Mapping Create SuperNode Generate User Input Node p Run From Here Click Edit to open the dialog box for the selected node Click Connect to manually connect one node to another Click Disconnect to delete all links to and from the node Click Rename and Annotate to open the Annotations tab of the editing dialog box Click New Comment to add a comment related to the node For more information see the topic Adding Comments and Annotations to Nodes and Streams on p 78 Click Disable Node to hide the node during processing To make the node visible again for processing click Enable Node For more information see the topic Disabling Nodes in a Stream on p 6 Click Cut or Delete to remove the selected node s from
263. ons such as date_weeks_difference Date1 Date2 This function returns the time in weeks from the date represented by the date string DATE to the date represented by the date string DATE2 as a real number This is based on a week of 7 0 days If DATE2 is prior to DATE1 this function returns a negative number Today s Date The current date can be added to the data set using the function TODAY Today s date is added as a string to the specified field or new field using the date format selected in the stream properties dialog box For more information see the topic Date and Time Functions in Chapter 8 on p 146 Summarizing Multiple Fields The CLEM language includes a number of functions that return summary statistics across multiple fields These functions may be particularly useful in analyzing survey data where multiple responses to a question may be stored in multiple fields For more information see the topic Working with Multiple Response Data on p 117 Comparison Functions You can compare values across multiple fields using the min_n and max_n functions for example max_n card1fee card2fee card3fee card4fee 116 Chapter 7 You can also use a number of counting functions to obtain counts of values that meet specific criteria even when those values are stored in multiple fields For example to count the number of cards that have been held for more than f
264. ons such as running optimization and time elapsed for model building and evaluation can easily be viewed using the Messages tab in the stream properties dialog box Error messages are also reported in this table To View Stream Messages gt On the File menu click Stream Properties or select the stream from the Streams tab in the managers pane right click and then click Stream Properties on the pop up menu gt Click the Messages tab Alternatively on the Tools menu click Stream Properties gt Messages 66 Chapter 5 Figure 5 22 Messages tab in stream properties dialog box i Stream execution started Setting Up Job Job Execution Started Overall Progress 5 Q Overall Progress 10 Overall Progress 15 Overall Progress 20 Overall Progress 35 Q Overall Progress 40 Overall Progress 45 Overall Progress 50 Job Execution Completed Model Drug building took 0 hours 0 minutes and 2 seconds In addition to messages regarding stream operations error messages are reported here When stream running is terminated because of an error this dialog box will open to the Messages tab with the error message visible Additionally the node with errors is highlighted in red on the stream canvas 67 Building Streams Figure 5 23 Stream running with error reported O mailshot5 X G Stream execution started Rad F i Stream executio
265. ons oarreriresinubecdan s niee En TAE E EEEE O eE Functions Handling Blanks and Null Values 0 0 0 0 cece ccc eee eee ees Special Fields sesede dd nat adhe ohare EE EEE Smee ends eed 9 Using IBM SPSS Modeler with a Repository 158 About the IBM SPSS Collaboration and Deployment Services Repository Storing and Deploying Repository Objects 0 cece eet ees Connecting to the Repository 0 0 cece ene e nee n ene nnn Entering Credentials for the Repository 0 0 ccc cece ete ete eens Browsing the Repository Contents 0 0 00sec cece cece etn e ene Storing Objects in the Repository 00 ccc cece teen tenes Setting Object Properties 0 cee teen e nets Sonno SEAMS ves sa Pee Fe aE WE D TS on ae Lia he aed a Storing Projets es ek toe ed ede wears ew Rae tanke a ied ea Minds a dled ech edhe kWickas Storing Nodes espant ws eee dada CMe beaded Gada wad a Maa ight de atals Storing Output Objects 0 6 cette E ens Storing Models and Model Palettes 0 cece cen eee nee es Retrieving Objects from the Repository 00 ccc cece teen ene eens Choosing an Objectto Retrieve 0 eet et ee enas Selecting an Object Version 0 2 0 cece eee A Searching for Objects inthe Repository 0 cece cece tent eens Modifying Repository Objects 0 00 ccc cent ne teen een neee Creating Renaming and Deleting Folders 00 0 cece cece eens Locking and
266. operty setting m Through a pop up menu in the stream m Using the keyboard You can scale the entire stream view to one of a number of sizes between 8 and 200 of the standard icon size 25 Figure 3 13 Changing the icon size A Save Stream Cres a tre covet sore Tya Save Stream As Crating 2s Store as Stream om ra Deploy a Close Stream Ants _ New Stream Ctri N Open Stream 3 Retrieve Stream Ctri O Eai New Comment X P Fx Select All Ctri Automatic Layout Print Ctrl P IBM SPSS Modeler Overview 200 150 100 Standard 92 83 75 Small O 67 58 50 46 42 37 25 017 012 8 To scale the entire stream stream properties method From the main menu choose Tools gt Stream Properties gt Options gt Layout Choose the size you want from the Icon Size menu Click Apply to see the result Click OK to save the change To scale the entire stream menu method Right click the stream background on the canvas Choose Icon Size and select the size you want To scale the entire stream keyboard method Press Ctrl on the main keyboard to zoom out to the next smaller size Press Ctrl Shift on the main keyboard to zoom in to the next larger size This feature is particularly useful for gaining an overall view of a complex stream You can also use it to minimize the number of pa
267. or Notification By turning on or off sounds you can control the way you are alerted to particular operations in the software For example you can activate sounds for events such as node creation and deletion or the generation of new output or models To set notification options on the Tools menu click User Options Click the Notifications tab Copyright IBM Corporation 1994 2012 236 237 Accessibility in IBM SPSS Modeler Controlling the Automatic Launching of New Windows The Notifications tab on the User Options dialog box is also used to control whether newly generated output such as tables and charts are launched in a separate window It may be easier for you to disable this option and open an output window only when required gt To set these options on the Tools menu click User Options gt Click the Notifications tab gt In the dialog box select New Output from the list in the Visual Notifications group gt Under Open Window select Never Node Size Nodes can be displayed using either a standard or small size You may want to adjust these sizes to fit your needs gt To set node size options on the File menu click Stream Properties gt Click the Layout tab gt From the Icon Size list select Standard Accessibility for Blind Users Support for blind users is predominately dependent on the use of a screen reader such as JAWS for Windows To optimize the use of a screen reader with IBM
268. or the Spacebar to select an item and then close the list You can also use the Escape key to close drop down lists that do not close when you have tabbed to another control Execution status When you are running a stream on a large database JAWS can lag behind in reading the stream status to you Press the Ctrl key periodically to update the status reporting Using the node palettes When you first enter a tab of the node palettes JAWS will sometimes read groupbox instead of the name of the node In this case you can use Ctrl Right Arrow and then Ctrl Left Arrow to reset the screen reader and hear the node name Reading menus Occasionally when you are first opening a menu JAWS may not read the first menu item If you suspect that this may have happened use the Down Arrow and then the Up Arrow to hear the first item in the menu Cascaded menus JAWS does not read the first level of a cascaded menu If you hear a break in speaking while moving through a menu press the Right Arrow key to hear the child menu items Additionally if you have IBM SPSS Modeler Text Analytics installed the following tips can make the interactive workbench interface more accessible to you Entering dialog boxes You may need to press the Tab key to put the focus on the first control upon entering a dialog box Exiting extended text boxes Use Ctrl Tab to exit extended text boxes and move to the next control Note Ctrl Tab is also used to exit tabl
269. ormation for selected version Name basklinks str Version 1 2008 09 03 08 07 30 996 Label Created By admin Creation Date Sep 3 2008 Keywords Description To select a specific version of a repository object gt Optional Sort the list by version label size creation date or creating user by double clicking on the header of the appropriate column 175 Using IBM SPSS Modeler with a Repository gt Select the object version you want to work with gt Click Continue Searching for Objects in the Repository You can search for objects by name folder type label date or other criteria Searching by Name To search for objects by name gt On the IBM SPSS Modeler main menu click Tools gt Repository gt Explore gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p 161 For specific port password and other connection details contact your local system administrator gt Click the Search tab gt Inthe Search for objects named field specify the name of the object you want to find Figure 9 14 Searching for objects by name 9 Repository Retrieve Search Search all fields Name Type Author Modified Ve L modelingintro str O Restrict search Contains ANY of the terms Must contain ALL of the terms
270. ory 170 prompts runtime 70 properties for data streams 54 project folder 207 report phases 209 purple nodes 60 pushbacks 60 Quality node missing values LOT radians measurements units 60 random function 141 random0 function 41 reals 27H128 records 29 missing values LOT 258 Index refresh source nodes 57 refreshing models 190 regression 245 rem function 138 renaming nodes 86 streams 74 replace function 41 replacing models replacing text 123 replicate function 141 reports adding to projects 202 generating 209 saving output 89 setting properties 209 resizing retrieving objects from the IBM SPSS Collaboration and Deployment Services Repository 172 rollover days 58 round function 138 rule sets evaluating 56 running streams 77 SAS files encoding 248 saving multiple objects 89 nodes 83 output objects 89 states 83 streams 88 scaling streams to view 24 scenarios 184 defined 160 deployment options 185 scientific notation display format 59 scoring branch 78 188 189 194 screen readers 23
271. ose this deployment type if you want to use this feature when running a stream from the repository For more information see the topic Mode Refresh on p 190 187 Using IBM SPSS Modeler with a Repository Scoring node Select a graph output or export node to identify the stream branch to be used for scoring the data While the stream can actually contain any number of valid branches models and terminal nodes one and only one scoring branch must be designated for purposes of deployment This is the most basic requirement to deploy any stream Scoring Parameters Allows you to specify parameters that can be modified when the scoring branch is run For more information see the topic Scoring and Modeling Parameters on p 188 Modeling node For model refresh specifies the modeling node used to regenerate or update the model in the repository Must be a modeling node of the same type as that specified for Model nugget Model Build Parameters Allows you to specify parameters that can be modified when the modeling node is run For more information see the topic Scoring and Modeling Parameters on p 188 Model nugget For model refresh specifies the model nugget that will be updated or regenerated each time the stream is updated in the repository typically as part of a scheduled job The model must be located on the scoring branch While multiple models may
272. oundaries before it allocates records to bins The data set is cached while the boundaries are computed then it is rescanned for allocation When the binning method is fixed width or mean standard deviation the data set is cached directly to disk These methods have a linear running time and require enough disk space to store the entire data set When the binning method is ranks or tiles the data set is sorted using the sort algorithm described earlier and the sorted data set is used as the cache Sorting gives these methods a running time of M N log N where M is the number of binned fields and N is the number of records it requires disk space equal to twice the data set size Generating a Derive node based on generated bins will improve performance in subsequent passes Derive operations are much faster than binning Merge by Key Join The Merge node when the merge method is keys equivalent to a database join sorts each of its input data sets by the key fields This part of the procedure has a running time of M N log N where M is the number of inputs and N is the number of records in the largest input it requires sufficient disk space to store all of its input data sets plus a second copy of the largest data set The running time of the merge itself is proportional to the size of the output data set which depends on the frequency of matching keys In the worst case where the output is the Cartesian product of the inputs the running tim
273. oungest_child Original Lists all fields in the template or existing stream all of the fields that are present further downstream Fields from the new data source will be mapped to these fields 96 Chapter 5 Mapped Lists the fields selected for mapping to template fields These are the fields whose names may have to change to match the original fields used in stream operations Click in the table cell for a field to activate a list of available fields If you are unsure of which fields to map it may be useful to examine the source data closely before mapping For example you can use the Types tab in the source node to review a summary of the source data Tips and Shortcuts Work quickly and easily by familiarizing yourself with the following shortcuts and tips Build streams quickly by double clicking Simply double click a node on the palette to add and connect it to the current stream m Use key combinations to select downstream nodes Press Ctrl Q and Ctrl W to toggle the selection of all nodes downstream m Use shortcut keys to connect and disconnect nodes When a node is selected in the canvas press F2 to begin a connection press Tab to move to the required node and press Shift Spacebar to complete the connection Press F3 to disconnect all inputs and outputs to the selected node m Customize the Nodes Palette tab with your favorite nodes On the Tools menu click Manage Palettes to open a dialog box fo
274. output In each of these windows or dialog boxes there is a tool on the toolbar that can be used to launch the output into your default browser which provides standard screen reader support You can then use the screen reader to convey the output information 246 Appendix A Accessibility in the Interactive Tree Window The standard display of a decision tree model in the Interactive Tree window may cause problems for screen readers To access an accessible version on the Interactive Tree menus click View gt Accessible Window This displays a view similar to the standard tree map but one which JAWS can read correctly You can move up down right or left using the standard arrow keys As you navigate the accessible window the focus in the Interactive Tree window moves accordingly Use the Spacebar to change the selection or use Ctrl Spacebar to extend the current selection Tips for Use There are several tips for making the IBM SPSS Modeler environment more accessible to you The following are general hints when working in SPSS Modeler Exiting extended text boxes Use Ctrl Tab to exit extended text boxes Note Ctrl Tab is also used to exit table controls Using the Tab key rather than arrow keys When selecting options for a dialog box use the Tab key to move between option buttons The arrow keys will not work in this context Drop down lists In a drop down list for dialog boxes you can use either the Escape key
275. over a wide variety of models from simple linear regression to complex multilevel models for non normal longitudinal data A generalized linear mixed model GLMM extends the linear model so that the target 11 New Features The Netezza Time Series node analyzes time series data and can predict future behavior from past events The Netezza Generalized Linear model expands the linear regression model so that the dependent variable is related to the predictor variables by means of a specified link function Moreover the model allows for the dependent variable to have a non normal distribution IBM SPSS Modeler Premium The EA Export node is a terminal node that reads entity data from a data source and exports the data to a repository for the purpose of entity resolution The Entity Analytics EA source node reads the resolved entities from the repository and passes this data to the stream for further processing such as formatting into a report The Streaming EA node compares new cases against the entity data in the repository The SNA Group Analysis node builds a model of a social network based on input data about the social groupings within the network This technique identifies links between the group members and analyzes the interactions within the groups to produce key performance indicators KPIs The KPIs can be used for purposes such as churn prediction anomaly detection or group leader identification
276. oying a stream one branch of the stream must be designated as the scoring branch that is the one containing the scoring node When you designate a branch as the scoring branch that branch is highlighted on the stream canvas as is the model link to the nugget on the scoring branch This visual representation is particularly useful in complex streams with multiple branches where the scoring branch might not be immediately obvious Note Only one stream branch can be designated as the scoring branch 189 Using IBM SPSS Modeler with a Repository Figure 9 26 Stream with scoring branch highlighted O G NewsChan sav Typ 4 AEWSCHAN 39 NEWSCHAN Analysis Tf the stream already had a scoring branch defined the newly designated branch replaces it as the scoring branch You can set the color of the scoring branch indication by means of a Custom Color option For more information see the topic Setting Display Options in Chapter 12 on p 220 You can show or hide the scoring branch indication by means of the Show hide stream markup toolbar button Figure 9 27 Show hide stream markup toolbar button 3 Identifying the Scoring Branch for Deployment You can designate the scoring branch either from the pop up menu of a terminal node or from the Tools menu If you use the pop up menu the scoring node is set automatically in the Deployment tab of the stream properties To designate a branch as the
277. oyment Services you can search through a list of servers or server clusters from the Server Login dialog box The ability to browse through the Statistics services running on a network is made available through the Coordinator of Processes Figure 3 2 Server Login dialog box Server Login Select add or edit the server to which you want to connect in the table By default the connection marked as Default is used at start up Defaut Server Name Description Fi Local Server Default data path SMODELERSER VER data a V Set Credentials Password Domain 14 Chapter 3 To Connect to a Server gt On the Tools menu click Server Login The Server Login dialog box opens Alternatively double click the connection status area of the SPSS Modeler window gt Using the dialog box specify options to connect to the local server computer or select a connection from the table m Click Add or Edit to add or edit a connection For more information see the topic Adding and Editing the IBM SPSS Modeler Server Connection on p 4 m Click Search to access a server or server cluster in the Coordinator of Processes For more information see the topic Searching for Servers in IBM SPSS Collaboration and Deployment Services on p 16 Server table This table contains the set of defined server connections The table displays the default connection serve
278. ply No to the message Do you want to save and close these files If you modify and save any associated files after the close of a project these updated versions will be included in the project the next time you open it To prevent this behavior remove the file from the project or save it under a different filename Generating a Report One of the most useful features of projects is the ability to generate reports based on the project items and annotations This is a critical component of effective data mining as discussed throughout the CRISP DM methodology You can generate a report directly into one of several file types or to an output window on the screen for immediate viewing From there you can print save or view the report in a web browser You can distribute saved reports to others in your organization Reports are often generated from project files several times during the data mining process for distribution to those involved in the project The report culls information about the objects referenced from the project file as well as any annotations created You can create reports based on either the Classes view or CRISP DM view 210 Chapter 11 Figure 11 9 Generated report window Project Report Report author sdunworth Report date Jul 31 2009 4 25 38 PM Project Information Project name Mortgage Retention Project Created by sdunworth Created on Feb 8 2004 5 19 24 PM Last modified by diones Las
279. pository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 164 Storing Projects You can store a complete IBM SPSS Modeler project as a cpj file in the repository so that it can be accessed by other users Because a project file is a container for other SPSS Modeler objects you need to tell SPSS Modeler to store the project s objects in the repository You do this using a setting in the Project Properties dialog box For more information see the topic Setting Project Properties in Chapter 11 on p 205 Once you configure a project to store objects in the repository whenever you add a new object to the project SPSS Modeler automatically prompts you to store the object When you have finished your SPSS Modeler session you must store a new version of the project file so that it remembers your additions The project file automatically contains and retrieves the latest versions of its objects If you did not add any objects to a project during an SPSS Modeler session then you do not have to re store the project file You must however store new versions for the project objects streams output and so forth that you changed To store a project gt Select the project on the CRISP DM or Classes tab in the managers pane in SPSS Modeler and on the
280. pter 7 Viewing or Selecting Values gt Field values can be viewed from a number of places in the system including the Expression Builder data audit reports and when editing future values in a Time Intervals node Note that data must be fully instantiated in a source or Type node to use this feature so that storage types and values are known Figure 7 9 Fields list with values shown for selected field g pression Builder Na_to_K Formula X Insert Value T Fieid Na Field Storage Max 0 896056 E ag Integer i Sex String BP String g Cholesterol String E K Real Poa Drug String g Na_to_K Unknown is_integer ITEM Returns a value of true if ITEM type is an integer Otherwise returns a value of false F Check expression before saving a emn Taa ten To view values for a field from the Expression Builder or a Time Intervals node select the required field and click the value picker button to open a dialog box listing values for the selected field You can then select a value and click Insert to paste the value into the current expression or list Figure 7 10 Value picker button For flag and nominal fields all defined values are listed For continuous numeric range fields the minimum and maximum values are displayed 123 Building CLEM Expressions Checking CLEM Expressions Click Check in the Expression Builder lower right corner to validate the expression Expressions that have not
281. r product with a set of conditions the purchase of several other products m Screening models can be used to screen data to locate fields and records that are most likely to be of interest in modeling and identify outliers that may not fit known patterns Available methods include feature selection and anomaly detection Data Manipulation and Discovery SPSS Modeler also includes many facilities that let you apply your expertise to the data Data manipulation Constructs new data items derived from existing ones and breaks down the data into meaningful subsets Data from a variety of sources can be merged and filtered m Browsing and visualization Displays aspects of the data using the Data Audit node to perform an initial audit including graphs and statistics Advanced visualization includes interactive graphics which can be exported for inclusion in project reports Statistics Confirms suspected relationships between variables in the data Statistics from IBM SPSS Statistics can also be used within SPSS Modeler m Hypothesis testing Constructs models of how the data behaves and verifies these models Copyright IBM Corporation 1994 2012 29 30 Chapter 4 Typically you will use these facilities to identify a promising set of attributes in the data These attributes can then be fed to the modeling techniques which will attempt to identify underlying rules and relationships Typical Applications Typical appl
282. r Window Using the dividers between various portions of the IBM SPSS Modeler interface you can resize or close tools to meet your preferences For example if you are working with a large stream you can use the small arrows located on each divider to close the nodes palette managers pane and project pane This maximizes the stream canvas providing enough work space for large or multiple streams Alternatively on the View menu click Nodes Palette Managers or Project to turn the display of these items on or off 24 Chapter 3 Figure 3 12 Maximized stream canvas File Edit Insert View Tools SuperNode Window Help 2H xabBernhZz re lt x RAG B Transactions Convegdates 2007 96 06 RFMApalysis remove scores RFM score descend 10000 highest RFM score Sort t E EE Transactional Data EEEE Binned and Scored Da cug Aggregated Data As an alternative to closing the nodes palette and the managers and project panes you can use the stream canvas as a scrollable page by moving vertically and horizontally with the scrollbars at the side and bottom of the SPSS Modeler window You can also control the display of screen markup which consists of stream comments model links and scoring branch indications To turn this display on or off click View gt Stream Markup Changing the icon size for a stream You can change the size of the stream icons in the following ways m Through a stream pr
283. r adding removing or moving the nodes shown on the Nodes Palette Figure 5 50 Palette Manager Palette Manager Palettes can be created and edited here To create edit sub palettes choose a palette and select the sub palettes button User defined palettes No of nodes Shown 16 9 9 17 9 29 4 4 M v E v M 7 cA m Rename nodes and add ToolTips Each node dialog box includes an Annotations tab on which you can specify a custom name for nodes on the canvas as well as add ToolTips to help organize your stream You can also include lengthy annotations to track progress save process details and denote any business decisions required or achieved 97 Building Streams Figure 5 51 ToolTip and custom node name m Insert values automatically into a CLEM expression Using the Expression Builder accessible from a variety of dialog boxes such as those for Derive and Filler nodes you can automatically insert field values into a CLEM expression Click the values button on the Expression Builder to choose from existing field values Figure 5 52 Values button Browse for files quickly When browsing for files on an Open dialog box use the File list click the yellow diamond button to access previously used directories as well as IBM SPSS Modeler default directories Use the forward and back buttons to scroll through accessed directories 98 Chapter 5 Figure 5 53 Select
284. r edited each time the model is updated These parameters are identified when you click the Model Build Parameters button on the Deployment tab of the stream properties dialog box m Modeling node Shows the name and type of the modeling node used to generate or update the model Previewing Stream Descriptions You can view the contents of a stream description in a web browser by clicking an option on the stream properties dialog box The contents of the description depend on the options you specify on the Deployment tab of the dialog box For more information see the topic Stream Deployment Options in Chapter 9 on p 185 To view a stream description On the main IBM SPSS Modeler menu click Tools gt Stream Properties gt Deployment Set the deployment type the designated scoring node and any scoring parameters If the deployment type is Model Refresh you can optionally select a m Modeling node and any model build parameters m Model nugget on the scoring branch of the stream Click the Preview Stream Description button 77 Building Streams Exporting Stream Descriptions You can export the contents of the stream description to an HTML file To export a stream description gt On the main menu click File gt Export Stream Description gt Enter a name for the HTML file and click Save Running Streams Once you have specified the required options for streams and connected
285. r name description and port number You can manually add a new connection as well as select or search for an existing connection To set a particular server as the default connection select the check box in the Default column in the table for the connection Default data path Specify a path used for data on the server computer Click the ellipsis button to browse to the required location Set Credentials Leave this box unchecked to enable the single sign on feature which attempts to log you in to the server using your local computer username and password details If single sign on is not possible or if you check this box to disable single sign on for example to log in to an administrator account the following fields are enabled for you to enter your credentials User ID Enter the user name with which to log on to the server Password Enter the password associated with the specified user name Domain Specify the domain used to log on to the server A domain name is required only when the server computer is in a different Windows domain than the client computer Click OK to complete the connection To Disconnect from a Server On the Tools menu click Server Login The Server Login dialog box opens Alternatively double click the connection status area of the SPSS Modeler window gt In the dialog box select the Local Server and click OK Adding and Editing the IBM SPSS Modeler Server Connection You can manually e
286. r the field Age is meaningless and should also be interpreted as a blank Frequently such obviously wrong values are purposely entered or fields left blank during a questionnaire to indicate a nonresponse At times you may want to examine these blanks more closely to determine whether a nonresponse such as the refusal to give one s age is a factor in predicting a specific outcome Some modeling techniques handle missing data better than others For example C5 0 and Apriori cope well with values that are explicitly declared as missing in a Type node Other modeling techniques have trouble dealing with missing values and experience longer training times resulting in less accurate models There are several types of missing values recognized by IBM SPSS Modeler m Null or system missing values These are nonstring values that have been left blank in the database or source file and have not been specifically defined as missing in a source or Type node System missing values are displayed as null Note that empty strings are not considered nulls in SPSS Modeler although they may be treated as nulls by certain databases m Empty strings and white space Empty string values and white space strings with no visible characters are treated as distinct from null values Empty strings are treated as equivalent to white space for most purposes For example if you select the option to treat white space as blanks in a source or Type no
287. r the Internet using the IBM SPSS Collaboration and Deployment Services Deployment Portal Setting Object Properties When you store an object the Repository Store dialog box is displayed enabling you to set the values of a number of properties for the object You can m Choose the name and repository folder under which the object is to be stored m Add information about the object such as the version label and other searchable properties m Assign one or more classification topics to the object m Set security options for the object The following sections describe the properties you can set 165 Using IBM SPSS Modeler with a Repository Choosing the Location for Storing Objects Figure 9 6 Choosing the location for storing an object Repository Store Repository rodev3 Save in Test z E dlentz_test igs_test New Folder gt Discriminant gm File name Markov FS gm Save in Shows the current folder the location where the object will be stored Double click a folder name in the list to set that folder as the current folder Use the Up Folder button to navigate to the parent folder Use the New Folder button to create a folder at the current level File name The name under which the object will be stored Store Stores the object at the current location Adding Information About Stored Objects All of the fields on this tab are optional 166 Chapter 9 Figure 9 7 Adding information
288. r to the default phase folder in CRISP DM view gt Alternatively you can drag and drop objects from the managers to the project pane Note You may be asked to save the object first When saving be sure that Add file to project is selected in the Save dialog box This will automatically add the object to the project after you save it Figure 11 4 Adding items to a project _ mE 9 9 Markov Markov FS Add To Stream Browse Rename and Annotate 6 Generate Modeling Node Save Model Save Model As 2S Store Model Mortgage Retention Project ios Business Understanding a D Presentation Sees amie EJ Data Understanding Addto Projet ios Data Preparation gt Delete Modeling B StartStream Evaluation a Deployment BatchMortgageRet SolnPublisher DeployDataBase 204 Chapter 11 Adding Nodes from the Canvas You can add individual nodes from the stream canvas by using the Save dialog box Select a node on the canvas Right click and click Save Node Alternatively on the main menu click Edit gt Node gt Save Node In the Save dialog box select Add file to project Create a name for the node and click Save This saves the file and adds it to the project Nodes are added to the Nodes folder in Classes view and to the default phase folder in CRISP DM view Adding External Files You can add a wide variety of non SPSS Modeler objects to a project Th
289. rations on any nondatabase data such as flat files Merge by order Balance Distinct operations in discard mode or where only a subset of fields are selected as distinct Any operation that requires accessing data from records other than the one being processed State and count field derivations History node operations Operations involving time series functions Type checking modes Warn and Abort Model construction application and analysis Note Decision trees rulesets linear regression and factor generated models can generate SQL and can therefore be pushed back to the database m Data output to anywhere other than the same database that is processing the data Node Caches To optimize stream running you can set up a cache on any nonterminal node When you set up a cache on a node the cache is filled with the data that passes through the node the next time you run the data stream From then on the data is read from the cache which is stored on disk in a temporary directory rather than from the data source Caching is most useful following a time consuming operation such as a sort merge or aggregation For example suppose that you have a source node set to read sales data from a database and an Aggregate node that summarizes sales by location You can set up a cache on the Aggregate node rather than on the source node because you want the cache to store the aggregated data rather than the entire data set Note Cachi
290. rbitrarily in CLEM expressions for example sqrt abs Signal max T1 T2 Baseline Brackets and operator precedence determine the order in which the expression is evaluated In this example the order of evaluation is m abs Signal is evaluated and sqrt is applied to its result m max T1 T2 is evaluated m The two results are multiplied x has higher precedence than m Finally Baseline is added to the result The descending order of precedence that is operations that are performed first to operations that are performed last is as follows m Function arguments Function calls XX x mod div rem gt lt gt lt j 112 Chapter 7 If you want to override precedence or if you are in any doubt of the order of evaluation you can use parentheses to make it explicit for example sqrt abs Signal max T1 T2 Baseline Stream Session and SuperNode Parameters Parameters can be defined for use in CLEM expressions and in scripting They are in effect user defined variables that are saved and persisted with the current stream session or SuperNode and can be accessed from the user interface as well as through scripting If you save a stream for example any parameters set for that stream are also saved This distinguishes them from local script variables which can be used only in the script in which they are declared Parameters are often used in scripting as part of a CLEM expr
291. rds and text to describe the project Folder Properties and Annotations gt gt Individual project folders in both CRISP DM and Classes view can be annotated In CRISP DM view this can be an extremely effective way to document your organization s goals for each phase of data mining For example using the annotation tool for the Business Understanding folder you can include documentation such as The business objective for this study is to reduce churn among high value customers This text could then be automatically included in the project report by selecting the Include in report option To annotate a folder Select a folder in the project pane Right click the folder and click Folder Properties In CRISP DM view folders are annotated with a summary of the purpose of each phase as well as guidance on completing the relevant data mining tasks You can remove or edit any of these annotations 208 Chapter 11 Figure 11 7 Project folder with CRISP DM annotation Data Understanding Name Data Understanding Tooltip text Data collection and analysis The data understanding involves collecting data in order to become familiar with the data identify data quality problems and identify initial insights or interesting subsets Include in report Gi cn Name This area displays the name of the selected field Tooltip text Create custom ToolTips that will be displayed when you hover the mouse pointer ov
292. ream Ctrl O 3 Retrieve Stream From this tab you can Access streams Save streams Save streams to the current project Close streams Open new streams Store and retrieve streams from an IBM SPSS Collaboration and Deployment Services repository if available at your site For more information see the topic About the IBM SPSS Collaboration and Deployment Services Repository in Chapter 9 on p 58 Right click a stream on the Streams tab to access these options Setting Options for Streams You can specify a number of options to apply to the current stream You can also save these options as defaults to apply to all your streams The options are as follows m General Miscellaneous options such as symbols and text encoding to use in the stream For more information see the topic Setting general options for streams on p 55 m Date Time Options relating to the format of date and time expressions For more information see the topic Setting date and time options for streams on p 57 m Number formats Options controlling the format of numeric expressions For more information see the topic Setting number format options for streams on p 59 Optimization Options for optimizing stream performance For more information see the topic Setting optimization options for streams on p 60 55
293. ream processing therefore when you have nodes that reduce the amount of data place them near the beginning of the stream IBM SPSS Modeler Server can apply some reordering rules automatically during compilation to bring forward certain nodes when it can be proven safe to do so This feature is enabled by default Check with your system administrator to make sure it is enabled in your installation When using SQL optimization you want to maximize its availability and efficiency Since optimization halts when the stream contains an operation that cannot be performed in the database it is best to group SQL optimized operations together at the beginning of the stream This strategy keeps more of the processing in the database so less data is carried into I BM SPSS Modeler The following operations can be done in most databases Try to group them at the beginning of the stream m Merge by key join Select Aggregate Sort Sample Append Distinct operations in include mode in which all fields are selected Filler operations Basic derive operations using standard arithmetic or string manipulation depending on which operations are supported by the database m Set to flag Copyright IBM Corporation 1994 2012 230 231 Performance Considerations for Streams and Nodes The following operations cannot be performed in most databases They should be placed in the stream after the operations in the preceding list Ope
294. redict a known result such as whether a customer will buy or leave or whether a transaction fits a known pattern of fraud Modeling techniques include machine learning rule induction subgroup identification statistical methods and multiple model generation 35 Understanding Data Mining Classification nodes A P The Auto Classifier node creates and compares a number of different models for binary outcomes yes or no churn or do not churn and so on allowing you to choose the best approach for a given analysis A number of modeling algorithms are supported making it possible to select the methods you want to use the specific options for each and the criteria for comparing the results The node generates a set of models based on the specified options and ranks the best candidates according to the criteria you specify The Auto Numeric node estimates and compares models for continuous numeric range outcomes using a number of different methods The node works in the same manner as the Auto Classifier node allowing you to choose the algorithms to use and to experiment with multiple combinations of options in a single modeling pass Supported algorithms include neural networks C amp R Tree CHAID linear regression generalized linear regression and support vector machines SVM Models can be compared based on correlation relative error or number of variables used The Classification and Regression C amp R Tree node g
295. redictable order For example a customer who purchases a razor and aftershave lotion may purchase shaving cream the next time he shops The Sequence node is based on the CARMA association rules algorithm which uses an efficient two pass method for finding sequences Segmentation Models Segmentation models divide the data into segments or clusters of records that have similar patterns of input fields As they are only interested in the input fields segmentation models have no concept of output or target fields Examples of segmentation models are Kohonen networks K Means clustering two step clustering and anomaly detection Segmentation models also known as clustering models are useful in cases where the specific result is unknown for example when identifying new patterns of fraud or when identifying groups of interest in your customer base Clustering models focus on identifying groups of similar records and labeling the records according to the group to which they belong This is done without the benefit of prior knowledge about the groups and their characteristics and it distinguishes clustering models from the other modeling techniques in that there is no predefined output or target field for the model to predict There are no right or wrong answers for these models Their value is determined by their ability to capture interesting groupings in the data and provide useful descriptions of those groupings Clustering models are o
296. reparation in SPSS Modeler and can be used in a wide range of nodes from record and field operations Select Balance Filler to plots and output Analysis Report Table For example you can use CLEM in a Derive node to create a new field based on a formula such as ratio Copyright IBM Corporation 1994 2012 105 106 Chapter 7 Figure 7 1 Derive node creating a new field based on a formula Mode Single Multiple Derive field Derive as Formula gt Fieldtype Y Defaut Formula Nak CLEM expressions can also be used for global search and replace operations For example the expression NULL FIELD can be used in a Filler node to replace system missing values with the integer value 0 To replace user missing values also called blanks use the BLANK function 107 Building CLEM Expressions Figure 7 2 Filler node replacing system missing values with O Fill in fields gi married E children Bil car S Condition NULL FIELD 3 More complex CLEM expressions can also be created For example you can derive new fields based on a conditional set of rules 108 Chapter 7 Figure 7 3 Conditional Derive comparing values of one field to those of the field before it Camm Derive as Conditional Mode Single Multiple Derive field ValueCategory1 Fieldtype lt Defautt gt If Cardi OFFSET CardiD 1 Then
297. requires sufficient disk space to store the entire data set but speeds up processing Evaluation The Evaluation node must sort the input data to compute tiles The sort is repeated for each model evaluated because the scores and consequent record order are different in each case The running time is M N log N where M is the number of models and N is the number of records Performance Modeling Nodes Neural Net and Kohonen Neural network training algorithms including the Kohonen algorithm make many passes over the training data The data is stored in memory up to a limit and the excess is spilled to disk Accessing the training data from disk is expensive because the access method is random which can lead to excessive disk activity You can disable the use of disk storage for these algorithms forcing all data to be stored in memory by selecting the Optimize for speed option on the Model tab of the node s dialog box Note that if the amount of memory required to store the data is greater than the working set of the server process part of it will be paged to disk and performance will suffer accordingly When Optimize for memory is enabled a percentage of physical RAM is allocated to the algorithm according to the value of the IBM SPSS Modeler Server configuration option Modeling memory limit percentage To use more memory for training neural networks either provide more RAM or increase the value of this option but note that setting the
298. resent a time or a timestamp time_in_secs TIME Integer Returns the time in seconds represented by TIME as an integer TIME can represent a time or a timestamp 150 Chapter 8 Function Result Description Returns the time difference in minutes between the times or timestamps represented by TIME and TIME2 as a real number If you select Rollover days mins in the stream properties dialog box a higher TIMER ins_difference TIME1 Real value of TIME is taken ts nies to the e p i or the previous hour if only minutes and seconds are specified in the current format If you do not select the rollover option a higher value of TIME will cause the returned value to be negative Returns the time difference in seconds between the times or timestamps represented by TIME1 and TIME2 as an integer If you select Rollover days mins in the stream properties dialog box a higher value i Integer of TIME is rite to refer to the E day or the previous hour if only minutes and seconds are specified in the current format If you do not select the rollover option a higher value of TIME causes the returned value to be negative Converting Date and Time Values Note that conversion functions and any other functions that require a specific type of input such as a date or time value depend on the current formats specified in the Stream Options dialog box For example if
299. ring integer and real types only For more information see the topic Working with Multiple Response Data in Chapter 7 on p IT7 Returns the last non null value in the supplied list of fields last_non_null LIST Any All storage types supported Returns the index of the last field in the specified LIST last_non_null_index LIST Integer containing a non null value or 0 if all values are null All storage types are supported max ITEM1 ITEM2 Any Returns the greater of the two items JTEM1 or ITEM2 Returns the index of the field containing the maximum value from a list of numeric fields or 0 if all values are null For example if the third field listed contains the max_index LIST Integer maximum the index value 3 is returned If multiple fields contain the maximum value the one listed first leftmost is returned For more information see the topic Working with Multiple Response Data in Chapter 7 on p L17 137 CLEM Language Reference Function Result Description Returns the maximum value from a list of numeric fields or null if all of the field values are null For more information max nist Number see the topic Summarizing Multiple Fields in Chapter 7 on p 15 Returns true if TEM is a member of the specified LIST member ITEM LIST Boolean Otherwise a false value is returned A list of field names can also be specified For more information see the topi
300. rom past data entity analytics focuses on improving the coherence and consistency of current data by resolving identity conflicts within the records themselves An identity can be that of an individual an organization an object or any other entity for which ambiguity might exist Identity resolution can be vital in a number of fields including customer relationship management fraud detection anti money laundering and national and international security IBM SPSS Modeler Social Network Analysis transforms information about relationships into fields that characterize the social behavior of individuals and groups Using data describing the relationships underlying social networks IBM SPSS Modeler Social Network Analysis identifies social leaders who influence the behavior of others in the network In addition you can determine which people are most affected by other network participants By combining these results with other measures you can create comprehensive profiles of individuals on which to base your predictive models Models that include this social information will perform better than models that do not IBM SPSS Modeler Text Analytics uses advanced linguistic technologies and Natural Language Processing NLP to rapidly process a large variety of unstructured text data extract and organize the key concepts and group these concepts into categories Extracted concepts and categories can be combined with existing structured data
301. rring Projects to the IBM SPSS Collaboration and Deployment Services Repository 204 Setting Project Properties 0 0 cect nett nee nes 205 Annotating a Project 00 0 ccc cee eee En ete n aa a a 206 Object POPE ties sc erreia wage aaa RE a sa ate nn OREA O EA EAA a aaa a 208 Closing a Projeti eccere ace dete ae else de Ae AR wanes nae aod 209 Generating a Repor sche add loes ba aime de ew baw ditaip es Heed eae totista pri 209 Saving and Exporting Generated Reports n n 00 0 0 ccc cence ete nes 212 12 Customizing IBM SPSS Modeler 215 Customizing IBM SPSS Modeler Options 0 0 ccc cee tee teen eens 215 Setting IBM SPSS Modeler Options 0 0 ccc etn tenet nena 215 System Options e t 0 tent e nent ene eens 215 Setting Default Directories 0 eee eee eens 216 Setting User Options 0 0 eect e nett nee nes 247 Setting User Information 00 0 0 ccc eee ene nee eens 222 viii Customizing the Nodes Palette 0 ccc cece tne nen enn Customizing the Palette Manager 0 c ccc c eect eeteeeenas Changing a Palette Tab View 0 0 cece nee ete eens CEMI Node Management 0 0 cece cent e etn een ene enn 13 Performance Considerations for Streams and Nodes 230 Order of NOd S8 i225 cians asetas hws Sewanee have Pe Gaia od aad ai ee ae eR eat ahd Node Caches tis 2 240082 wcteaees sented ole 24 are whee Seer Eee ode ds deka Peed Performance Process NOd S
302. rsioning metadata and search capabilities Note A separate license is required to access an IBM SPSS Collaboration and Deployment Services repository For more information see http www ibm com software analytics spss products deployment cds Before you can use SPSS Modeler with the repository you need to install an adapter at the repository host Without this adapter you may see the following message when attempting to access repository objects from certain SPSS Modeler nodes or models The repository may need updating to support new node model and output types For instructions on installing the adapter see the SPSS Modeler Deployment Installation guide available on the SPSS Modeler Deployment DVD Details of how to access SPSS Modeler repository objects from IBM SPSS Collaboration and Deployment Services Deployment Manager are given in the SPSS Modeler Deployment Guide The following sections provide information on accessing the repository from within SPSS Modeler Copyright IBM Corporation 1994 2012 158 159 Using IBM SPSS Modeler with a Repository Figure 9 1 Objects in the IBM SPSS Collaboration and Deployment Services Repository O Repository admin rodev3 Go Wie 3 Est Type Size Version _ Labels Last Modified Author o 35agedDefectr Stream 13 KB 0 2007 11 1 none Mon Nov 12 20 AGVWALTNEY Can_be_deleted analysis of _ch Output 2KB 0 2008 12 1 none Fri Dec
303. rt generated to the screen is displayed in a new output window Any graphs included in the report are displayed as in line images 213 Projects and Reports The total number of nodes in each stream is listed within the report The numbers are shown under the following headings which use IBM SPSS Modeler terminology not CRISP DM terminology m Data readers Source nodes Data writers Export nodes Model builders Build or Modeling nodes Model appliers Generated models also known as nuggets Output builders Graph or Output nodes Other Any other nodes related to the project For example those available on the Field Ops tab or Record Ops tab on the Nodes Palette To save a report On the File menu click Save Specify a filename The report is saved as an output object To export a report On the File menu click Export and the file type to which you want to export Specify a filename The report is saved in the format you chose You can export to the following file types HTML m Text Microsoft Word Microsoft Excel Microsoft PowerPoint Note To export to a Microsoft Office file you must have the corresponding application installed Use the buttons at the top of the window to m Print the report m View the report as HTML in an external web browser 214 Chapter 11 Figure 11 11 Report displayed in a web browser Business Understanding The purpose of this project is to
304. rting a model in PMML format Open Model Ss Retrieve Model Load Palette Ee Retrieve Palette Save Palette 2s Store Palette Clear Palette Add Palette to Project gt Select the file to import and specify options for variable labels as required gt Click Open 198 Chapter 10 Figure 10 3 Selecting the XML file for a model saved using PMML BU 000E Class xml lt Increase xml 4 pep xml E Use variable labels if present in model File Name Files of Type XML Files xm Use variable labels if present in model The PMML may specify both variable names and variable labels such as Referrer ID for RefID for variables in the data dictionary Select this option to use variable labels if they are present in the originally exported PMML If you have selected the variable label option but there are no variable labels in the PMML the variable names are used as normal Model Types Supporting PMML PMML Export SPSS Modeler models The following models created in IBM SPSS Modeler can be exported as PMML 4 0 mE C amp R Tree m QUEST m CHAID m Linear Regression 199 Exporting to External Applications Neural Net C5 0 Logistic Regression Genlin SVM Bayes Net Apriori Carma K Means Kohonen TwoStep KNN Statistics Model The following model created in SPSS Modeler can be exported as PMML 3 2 m Decision List Database native models For
305. rules provide a list of best practices to use when creating expressions m Strings Always use double quotes when writing strings Type 2 or value Single quotes can be used instead but at the risk of confusion with quoted fields 111 Building CLEM Expressions m Characters Always use single backquotes like this For example note the character d in the function stripchar d drugA The only exception to this is when you are using an integer to refer to a specific character in a string For example note the character 5 in the function lowertoupper druga 5 gt A Note On a standard U K and U S keyboard the key for the backquote character grave accent Unicode 0060 can be found just below the Esc key m Fields Fields are typically unquoted when used in CLEM expressions subscr 2 arraylD gt CHAR You can use single quotes when necessary to enclose spaces or other special characters Order Number Fields that are quoted but undefined in the data set will be misread as strings m Parameters Always use single quotes P threshold Expressions and Conditions CLEM expressions can return a result used when deriving new values for example Weight 2 2 Age 1 sqrt Signal Echo Or they can evaluate true or false used when selecting on a condition for example Drug drugA Age lt 16 not PowerFlux and Power gt 2000 You can combine operators and functions a
306. s on the stream canvas When a SuperNode annotation is converted to a comment the comment is not attached to the SuperNode on the stream canvas but is visible when you zoom in to the SuperNode To convert a stream annotation to a comment gt Click Stream Properties on the Tools menu Alternatively you can right click a stream in the managers pane and click Stream Properties 86 Chapter 5 gt Click the Annotations tab gt Select the Show annotation as comment check box gt Click OK To convert a SuperNode annotation to a comment Double click the SuperNode icon on the canvas Click the Annotations tab Select the Show annotation as comment check box vyv v vy y Click OK Annotations Nodes streams and models can be annotated in a number of ways You can add descriptive annotations and specify a custom name These options are useful especially when generating reports for streams added to the project pane For nodes and model nuggets you can also add ToolTip text to help distinguish between similar nodes on the stream canvas Adding Annotations Editing a node or model nugget opens a tabbed dialog box containing an Annotations tab used to set a variety of annotation options You can also open the Annotations tab directly gt To annotate a node or nugget right click the node or nugget on the stream canvas and click Rename and Annotate The editing dialog box opens with the Annotations tab visible gt
307. s such as display fonts and colors by clicking User Options on the Tools gt Options menu m Specify the location of applications that work with SPSS Modeler by clicking Helper Applications on the Tools gt Options menu m Specify the default directories used in SPSS Modeler by clicking Set Directory or Set Server Directory on the File menu You can also set options that apply to some or all of your streams For more information see the topic Setting Options for Streams in Chapter 5 on p 54 System Options You can specify the preferred language or locale for IBM SPSS Modeler by clicking System Options on the Tools gt Options menu Here you can also set the maximum memory usage for SPSS Modeler Note that changes made in this dialog box will not take effect until you restart SPSS Modeler Copyright IBM Corporation 1994 2012 215 216 Chapter 12 Figure 12 1 System Options dialog box System Options X Maximum memory MB E Use system locale Note changes will take effect when the program is restarted od a Maximum memory Select to impose a limit in megabytes on SPSS Modeler s memory usage On some platforms SPSS Modeler limits its process size to reduce the toll on computers with limited resources or heavy loads If you are dealing with large amounts of data this may cause an out of memory error You can ease memory load by specifying a new threshold Use system
308. s focuses on improving the coherence and consistency of current data by resolving identity conflicts within the records themselves An identity can be that of an individual an organization an object or any other entity for which ambiguity might exist Identity resolution can be vital in a number of fields including customer relationship management fraud detection anti money laundering and national and international security IBM SPSS Modeler Social Network Analysis transforms information about relationships into fields that characterize the social behavior of individuals and groups Using data describing the relationships underlying social networks IBM SPSS Modeler Social Network Analysis identifies social leaders who influence the behavior of others in the network In addition you can determine which people are most affected by other network participants By combining these results with other measures you can create comprehensive profiles of individuals on which to base your predictive models Models that include this social information will perform better than models that do not Note SPSS Modeler Professional must be installed before installing any of the SPSS Modeler Premium features New Nodes in This Release IBM SPSS Modeler Professional can have a non normal distribution is linearly related to the factors and covariates via a specified link function and so that the observations can be correlated Generalized linear mixed models c
309. s modeling However decisions made and information gathered during the modeling phase can often lead you to rethink parts of the data preparation phase which can then present new modeling issues The two phases feed back on each other until both phases 34 Chapter 4 have been resolved adequately Similarly the evaluation phase can lead you to reevaluate your original business understanding and you may decide that you have been trying to answer the wrong question At this point you can revise your business understanding and proceed through the rest of the process again with a better target in mind The second key point is the iterative nature of data mining You will rarely if ever simply plan a data mining project complete it and then pack up your data and go home Data mining to address your customers demands is an ongoing endeavor The knowledge gained from one cycle of data mining will almost invariably lead to new questions new issues and new opportunities to identify and meet your customers needs Those new questions issues and opportunities can usually be addressed by mining your data once again This process of mining and identifying new opportunities should become part of the way you think about your business and a cornerstone of your overall business strategy This introduction provides only a brief overview of the CRISP DM process model For complete details on the model consult the following resources m The CRISP
310. s the number of non null values from a list of fields date_before DATE1 Bool Used to check the ordering of date values Returns a true DATE2 oer value if DATE is before DATE2 Returns the index of the first field containing ITEM from a LIST of fields or 0 if the value is not found Supported for first_index ITEM LIST Integer string integer and real types only For more information see the topic Working with Multiple Response Data in Chapter 7 on p 17 Returns the first non null value in the supplied list of fields first_non_null LIST Any All storage types supported Returns the index of the first field in the specified LIST first_non_null_index LIST Integer containing a non null value or 0 if all values are null All storage types are supported ITEM1 ITEM2 Boolean Returns true for records where ITEM is equal to ITEM2 ITEM1 ITEM2 Boolean Returns true if the two strings are not identical or 0 if they are identical ITEM1 lt ITEM2 Boolean Returns true for records where ITEM is less than ITEM2 2 Returns true for records where ITEM is less than or equal ITEM1 lt ITEM2 Boolean to ITEM2 ITEM1 gt ITEM2 Boolean Returns true for records where JTEM is greater than ITEM2 k Returns true for records where ITEM 1 is greater than or ITEM1 gt ITEM2 Boolean equal to ITEM2 Returns the index of the last field containing ITEM from a LIST of fields or 0 if the value is not found Supported for last_index ITEM LIST Integer st
311. s used to read process and output data in different formats Effectively this means all nodes other than modeling nodes m IBM SPSS Modeler Modeling Nodes Descriptions of all the nodes used to create data mining models IBM SPSS Modeler offers a variety of modeling methods taken from machine learning artificial intelligence and statistics m IBM SPSS Modeler Algorithms Guide Descriptions of the mathematical foundations of the modeling methods used in SPSS Modeler This guide is available in PDF format only m IBM SPSS Modeler Applications Guide The examples in this guide provide brief targeted introductions to specific modeling methods and techniques An online version of this guide is also available from the Help menu For more information see the topic Application xamples on p 5 m IBM SPSS Modeler Scripting and Automation Information on automating the system through scripting including the properties that can be used to manipulate nodes and streams m IBM SPSS Modeler Deployment Guide Information on running SPSS Modeler streams and scenarios as steps in processing jobs under IBM SPSS Collaboration and Deployment Services Deployment Manager m IBM SPSS Modeler CLEF Developer s Guide CLEF provides the ability to integrate third party programs such as data processing routines or modeling algorithms as nodes in SPSS Modeler m IBM SPSS Modeler In Database Mining Guide Inform
312. sary gt Click Deploy as stream to deploy the stream for use with IBM SPSS Modeler Advantage or IBM SPSS Collaboration and Deployment Services Click Deploy as scenario to deploy the stream for use with IBM SPSS Collaboration and Deployment Services or Predictive Applications version 5 gt Click Store For more information click Help gt Continue from Completing the deployment process To deploy the current stream Tools menu method gt On the main menu click Tools gt Stream Properties gt Deployment gt Choose the deployment type complete the rest of the Deployment tab as necessary and click Store For more information see the topic Stream Deployment Options on p 1185 Completing the deployment process gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator 185 Using IBM SPSS Modeler with a Repository Figure 9 23 Storing a stream in the repository Repository Store a Repository rodev3 ri exportcsy str B LongNodeName str MissingNodes str Model Discriminant str B Model GeneralizedLinear str B modelingintro str B cc_c51response str B newschancart_commented str File name baye sore canc He gt Inthe Repository Store dialog box choose
313. scoring branch pop up menu gt Connect the model nugget to a terminal node a processing or output node downstream from the nugget gt Right click the terminal node gt On the menu click Use as Scoring Branch 190 Chapter 9 To designate a branch as the scoring branch Tools menu Connect the model nugget to a terminal node a processing or output node downstream from the nugget On the main menu click Tools gt Stream Properties gt Deployment On the Deployment type list click Scoring Only or Model Refresh as required For more information see the topic Stream Deployment Options on p 185 Click the Scoring node field and select a terminal node from the list Click OK Model Refresh Model refresh is the process of rebuilding an existing model in a stream using newer data The stream itself does not change in the repository For example the algorithm type and stream specific settings remain the same but the model is retrained on new data and updated if the new version of the model works better than the old one Only one model nugget in a stream can be set to refresh this is known as the refresh model If you click the Model Refresh option on the Deployment tab of the stream properties see Stream Deployment Options on p 185 the model nugget that you designate at that time becomes the refresh model You can also designate a model as the refresh model from the pop up menu of a model nug
314. session parameters dialog box They are available to all streams used in the current session all streams listed on the Streams tab in the managers pane 69 Building Streams Parameters can also be set for SuperNodes in which case they are visible only to nodes encapsulated within that SuperNode To Set Stream and Session Parameters through the User Interface gt To set stream parameters on the main menu click Tools gt Stream Properties gt Parameters gt To set session parameters click Set Session Parameters on the Tools menu Figure 5 25 Setting parameters for the session Session Parameters Prompt Name Long name Storage Value Type Minvalue Minimum value oO Integer 50 no val I MaxYalue Maximum value re Integer 75 no val 5 SrveCode Service code os No E m Typelesy L Cont inua 8 Flag Specify HOONHF Prompt Check this box if you want the user to be prompted at runtime to enter a value for this parameter Name Parameter names are listed here You can create a new parameter by entering a name in this field For example to create a parameter for the minimum temperature you could type minvalue Do not include the P prefix that denotes a parameter in CLEM expressions This name is also used for display in the CLEM Expression Builder Long name Lists the descriptive name for each parameter created Storage Select a storage type from the list Storage indi
315. sibility features 236 documentation 4 getting started 12 255 options 215 overview 12 running from command line 13 tips and shortcuts IBM SPSS Modeler Advantage 160 184 IBM SPSS Modeler Server domain name Windows 13 host name 3H14 password 13 port number 3H14 user ID IBM SPSS Statistics models B9 icons setting options 24 64 if then else functions importing PMML 97HI98 INDEX function 152 137 INDEX function 150 152 information functions integer_bitcount function 140 integer_leastbit function 140 integer_length function 140 integers I27 128 134 Interactive Tree window accessibility 246 intof function 138 introduction 127 IBM SPSS Modeler I2 215 is_date function 134 is_datetime function 134 is_integer function 134 is_number function 134 is_real function 134 is_string function 134 is_time function 134 is_timestamp function 134 isalphacode function 41 isendstring function I 41 islowercode f
316. ss than or equal to ITEM2 Used between two integers Equivalent to the Boolean expression INT1 amp amp INT2 0 Used between two integers Equivalent to the Boolean expression INT1 amp amp INT2 0 Adds two numbers NUM1 NUM2 Concatenates two strings for example STRING1 gt lt STRING2 Subtracts one number from another NUMI NUM2 Can also be used in front of a number NUM Used to multiply two numbers NUM1 NUM2 132 Chapter 8 Operation Comments Precedence see next section amp amp Used between two integers The result is the bitwise and of the integers INT1 and INT2 4 amp a Used between two integers The result is the bitwise and of INT1 and the bitwise complement of INT2 Used between two integers The result is the bitwise inclusive or of INT1 and INT2 Used in front of an integer Produces the bitwise complement of INT amp Used between two integers The result is the bitwise exclusive or of INT1 and INT2 INT1 lt lt N Used between two integers Produces the bit pattern of INT shifted left by N positions INT1 gt gt N Used between two integers Produces the bit pattern of INT shifted right by N positions Used to divide one number by another NUMI NUM2 Used between two numbers BASE POWER Returns BASE raised to the po
317. st be constant the third argument is pointless and the two argument version of this function should be used See also the note about self referential functions in the two argument version described earlier SDEV FIELD Real Returns the standard deviation of values for the specified FIELD or FIELDS SDEV FIELD EXPR Real Returns the standard deviation of values for FIELD over the last EXPR records received by the current node including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 If EXPR is omitted or if it exceeds the number of records received so far the standard deviation over all of the records received so far is returned SDEV FIELD EXPR INT Real Returns the standard deviation of values for FIELD over the last EXPR records received by the current node including the current record FIELD must be the name of a numeric field EXPR may be any expression evaluating to an integer greater than 0 If EXPR is omitted or if it exceeds the number of records received so far the standard deviation over all of the records received so far is returned INT specifies the maximum number of values to look back This is far more efficient than using just two arguments SINCE EXPR Returns the number of records that have passed since EXPR an arbitrary CLEM expression was true SINCE EXPR INT Adding the second
318. such as demographics and applied to modeling using the full suite of SPSS Modeler data mining tools to yield better and more focused decisions 4 Chapter 1 IBM SPSS Modeler Documentation Documentation in online help format is available from the Help menu of SPSS Modeler This includes documentation for SPSS Modeler SPSS Modeler Server and SPSS Modeler Solution Publisher as well as the Applications Guide and other supporting materials Complete documentation for each product including installation instructions is available in PDF format under the Documentation folder on each product DVD Installation documents can also be downloaded from the web at ittp www 0L ibm com support docview wss uid swg2 023172 Documentation in both formats is also available from the SPSS Modeler Information Center at http publib boulder ibm com infocenter spssmodl v 15r0m0 SPSS Modeler Professional Documentation The SPSS Modeler Professional documentation suite excluding installation instructions is as follows m IBM SPSS Modeler User s Guide General introduction to using SPSS Modeler including how to build data streams handle missing values build CLEM expressions work with projects and reports and package streams for deployment to IBM SPSS Collaboration and Deployment Services Predictive Applications or IBM SPSS Modeler Advantage m IBM SPSS Modeler Source Process and Output Nodes Descriptions of all the node
319. sult Description arccos NUM Real Computes the arccosine of the specified angle arccosh NUM Real Computes the hyperbolic arccosine of the specified angle arcsin NUM Real Computes the arcsine of the specified angle arcsinh NUM Real Computes the hyperbolic arcsine of the specified angle arctan NUM Real Computes the arctangent of the specified angle Computes the arctangent of NUM_Y NUM_X and uses the arctan2 NUM_Y Real signs of the two numbers to derive quadrant information The NUM_X result is a real in the range pi lt ANGLE lt pi radians 180 lt ANGLE lt 180 degrees arctanh NUM Real Computes the hyperbolic arctangent of the specified angle cos NUM Real Computes the cosine of the specified angle cosh NUM Real Computes the hyperbolic cosine of the specified angle pi Real This constant is the best real approximation to pi sin NUM Real Computes the sine of the specified angle sinh NUM Real Computes the hyperbolic sine of the specified angle tan NUM Real Computes the tangent of the specified angle tanh NUM Real Computes the hyperbolic tangent of the specified angle Probability Functions Probability functions return probabilities based on various distributions such as the probability that a value from Student s t distribution will be less than a specific value Function Result Description Returns the probability that a value from the chi square cdf_chisq NUM DF Real distributio
320. t A connection icon is displayed both on the start node and the cursor Click a second node on the canvas to connect the two nodes Figure 5 4 Connecting nodes using the Connect option from the pop up menu Database Derive C 45 Building Streams Figure 5 5 Connected nodes 2 Database Derive When connecting nodes there are several guidelines to follow You will receive an error message if you attempt to make any of the following types of connections m A connection leading to a source node A connection leading from a terminal node A node having more than its maximum number of input connections Connecting two nodes that are already connected Circularity data returns to a node from which it has already flowed Bypassing Nodes in a Stream When you bypass a node in the data stream all of its input and output connections are replaced by connections that lead directly from its input nodes to its output nodes If the node does not have both input and output connections then all of its connections are deleted rather than rerouted For example you might have a stream that derives a new field filters fields and then explores the results in a histogram and table If you want to also view the same graph and table for data before fields are filtered you can add either new Histogram and Table nodes to the stream or you can bypass the Filter node When you bypass the Filter node the connections to the graph and t
321. t can be either a string or character and is used in this function to return a new item of the same type with any uppercase characters uppertolower CHAR CHAR or converted to their lowercase equivalents uppertolower STRING String Note Remember to specify strings with double quotes and characters with single backquotes Simple field names should be specified without quotes SoundEx Functions SoundEx is a method used to find strings when the sound is known but the precise spelling is not Developed in 1918 it searches out words with similar sounds based on phonetic assumptions about how certain letters are pronounced It can be used to search names in a database for example where spellings and pronunciations for similar names may vary The basic SoundEx algorithm is documented in a number of sources and despite known limitations for example leading letter combinations such as ph and f will not match even though they sound the same is supported in some form by most databases Function Result Description soundex STRING Integer Returns the four character SoundEx code for the specified STRING Returns an integer between 0 and 4 that indicates the number of characters that are the same in the SoundEx encoding for the two strings where 0 indicates no similarity and 4 indicates strong similarity or identical strings soundex_difference STRING1 STRING2 Integer Date and Time Functions CLEM includes a f
322. t modified on Jun 25 2009 2 46 46 PM Description Uses predictive modeling to determine which mortgage customers are likely to churn at the end of their discounted period which customers will switch to a new rate and which will stay inert Business Understanding This initial phase focuses on understanding the project objectives and requirements from a business perspective To generate a report gt Select the project folder in either CRISP DM or Classes view gt Right click the folder and click Project Report gt Specify the report options and click Generate Report 211 Projects and Reports Figure 11 10 Selecting options for a report a Mortgage Retention Project X Report Format Output name Auto O Custom File type Report Structure Title Project Report Report structure CRISP D Author sdunworth Report includes only items marked for inclusion in the report O only items marked for exclusion from the report O all folders and objects all tems O recent items b days old or less O old items days old or more Order by The options in the report dialog box provide several ways to generate the type of report you need Output name Specify the name of the output window if you choose to send the output of the report to the screen You can specify a custom name or let IBM SPSS Modeler automatically name the window for you Output to screen Select this
323. t the result is indistinguishable from a quoted field referrerlD For more information see the topic String Functions on p 141 A list is an ordered sequence of elements which may be of mixed type Lists are enclosed in square brackets Examples of lists are 1 2 4 16 and abc def Lists are not used as the value of IBM SPSS Modeler fields They are used to provide arguments to functions such as member and oneof Names in CLEM expressions that are not names of functions are assumed to be field names You can write these simply as Power val27 state_flag and so on but if the name begins with a digit or includes non alphabetic characters such as spaces with the exception of the underscore place the name within single quotation marks for example Power Increase 2nd answer 101 P NextField Note Fields that are quoted but undefined in the data set will be misread as strings Date calculations are based on a baseline date which is specified in the stream properties dialog box The default baseline date is 1 January 1900 For more information see the topic Setting general options for streams in Chapter 5 on p 55 The CLEM language supports the following date formats Format Examples DDMMYY 150163 MMDDYY 011563 YYMMDD 630115 YYYYMMDD 19630115 YYYYDDD Four digit year followed by a three digit number representing the d
324. t until you have added all the nodes you want After you have added all of the required nodes you can change the order in which they are displayed on the palette tab gt Use the simple arrow buttons to move a node up or down one row gt Use the line arrow buttons to move a node to the bottom or top of the list gt To remove a node from a palette highlight the node and click the Delete button to the right of the Selected nodes area Displaying Palette Tabs on the Nodes Palette There may be options available within IBM SPSS Modeler that you never use in this case you can use the Palette Manager to hide the tabs containing these nodes 226 Chapter 12 Figure 12 8 Palette Manager showing the tabs displayed on the Nodes Palette Palette Manager Palettes can be created and edited here To create edit sub palettes choose a palette and select the sub palettes button User defined palettes No of nodes Shown 16 9 9 17 Fi Ti Fi 9 Fi Fi Fi Ti Ti 29 A To select which tabs are to be shown on the Nodes Palette gt From the Tools menu open the Palette Manager gt Using the check boxes in the Shown column select whether to include or hide each palette tab To permanently remove a palette tab from the Nodes Palette highlight the node and click the Delete button to the right of the Shown column Once deleted a palette tab cannot be recovered Note You cannot delete the default
325. t work ask your system administrator for the correct port number Description Enter an optional description for this server connection Ensure secure connection use SSL Specifies whether an SSL Secure Sockets Layer connection should be used SSL is a commonly used protocol for securing data sent over a network To use this feature SSL must be enabled on the server hosting IBM SPSS Modeler Server If necessary contact your local administrator for details To Edit Server Connections On the Tools menu click Server Login The Server Login dialog box opens In this dialog box select the connection you want to edit and then click Edit The Server Login Add Edit Server dialog box opens Change the server connection details and click OK to save the changes and return to the Server Login dialog box 16 Chapter 3 Searching for Servers in IBM SPSS Collaboration and Deployment Services Instead of entering a server connection manually you can select a server or server cluster available on the network through the Coordinator of Processes available in I BM SPSS Collaboration and Deployment Services A server cluster is a group of servers from which the Coordinator of Processes determines the server best suited to respond to a processing request Although you can manually add servers in the Server Login dialog box searching for available servers lets you connect to servers without requiring that you know the correct server na
326. ted gt To permanently remove a subpalette from the palette tab highlight the subpalette and click the Delete button to the right of the Shown column Note You cannot delete the default subpalettes supplied with the Modeling palette tab Changing the display order on the Palette Tab After you have selected which subpalettes you want to display you can change the order in which they are displayed on the parent palette tab gt Use the simple arrow buttons to move a subpalette up or down one row gt Use the line arrow buttons to move a subpalette to the bottom or top of the list The subpalettes you create are displayed on the Nodes Palette when you select their parent palette tab For more information see the topic Changing a Palette Tab View on p 228 Creating a Subpalette Because you can add any existing node to the custom palette tabs that you create it is possible that you will select more nodes than can be easily displayed on screen without scrolling To prevent having to scroll you can create subpalettes into which you place the nodes you chose for 228 Chapter 12 v v v Yy v v v YV the palette tab For example if you created a palette tab that contains the nodes you use most frequently for creating your streams you could create four subpalettes that break the selections down by source node field operations modeling and output Note You can only select subpalette nodes from thos
327. ter 8 Function Result Description GLOBAL_MIN FIELD Number Returns the minimum value for FIELD over the whole data set as previously generated by a Set Globals node FIELD must be the name of a numeric field If the corresponding global value has not been set an error occurs GLOBAL_SDEV FIELD Number Returns the standard deviation of values for FIELD over the whole data set as previously generated by a Set Globals node FIELD must be the name of a numeric field If the corresponding global value has not been set an error occurs GLOBAL_MEAN FIELD Number Returns the mean average of values for FIELD over the whole data set as previously generated by a Set Globals node FIELD must be the name of a numeric field If the corresponding global value has not been set an error occurs GLOBAL_SUM FIELD Number Returns the sum of values for FIELD over the whole data set as previously generated by a Set Globals node FIELD must be the name of a numeric field If the corresponding global value has not been set an error occurs Functions Handling Blanks and Null Values Using CLEM you can specify that certain values in a field are to be regarded as blanks or missing values The following functions work with blanks Note functions cannot be called from scripts Function Result Description BLANK FIELD Boolean Returns true for all records whose va
328. ter 9 on p 184 gt Click the Open in IBM SPSS Modeler Advantage toolbar button or from the main menu click File gt Open in IBM SPSS Modeler Advantage Copyright IBM Corporation 1994 2012 195 196 Chapter 10 gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository in Chapter 9 on p 161 For specific port password and other connection details contact your local system administrator Note The repository server must also have the IBM SPSS Modeler Advantage software installed gt Inthe Repository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties in Chapter 9 on p 164 Doing so launches IBM SPSS Modeler Advantage with the stream already open The stream is closed in SPSS Modeler Importing and Exporting Models as PMML PMML or predictive model markup language is an XML format for describing data mining and statistical models including inputs to the models transformations used to prepare data for data mining and the parameters that define the models themselves IBM SPSS Modeler can import and export PMML making it possible to share models with other applications that support this format such as IBM
329. the Annotations tab of the object A repository search by description or keyword does not return information from the Annotations tab For more information see the topic Searching for Objects in the Repository jon p 175 167 Using IBM SPSS Modeler with a Repository Assigning Topics to a Stored Object Topics are a hierarchical classification system for the content stored in the repository You can choose from the available topics when storing objects and users can also search for objects by topic The list of available topics is set by repository users with the appropriate privileges for more information see the Deployment Manager User s Guide Figure 9 8 Assigning topics to an object Repository Store Topics OQLTest Autos Cars fQLTestiAutos SUYs OLTest Autos Trucks To assign a topic to the object gt Click the Add button gt Click a topic name from the list of available topics gt Click OK To remove a topic assignment gt Select the topic in the list of assigned topics gt Click Delete Setting Security Options for Stored Objects You can set or change a number of security options for a stored object For one or more principals that is users or groups of users you can m Assign access rights to the object m Modify access rights to the object m Remove access rights to the object 168 Chapter 9 Figure 9 9 Setting security options for
330. the drop down list to display a subset of functions or operators Available functions are grouped into categories for easier searching Figure 7 7 Functions drop down list Expression Builder Na_to_K Formula Sex String BP String Cholesterol String Na Real K Real Drug String is_integer ITEM Returns a value of true if ITEM type is an integer Otherwise returns a value of false T Check expression before saving Lo canen Most of these categories are described in the Reference section of the CLEM language description For more information see the topic Functions Reference in Chapter 8 on p 133 The other categories are as follows General Functions contains a selection of some of the most commonly used functions Recently Used contains a list of CLEM functions used within the current session Functions contains a list of all the special functions which have their names preceded by an sign Database Functions If the stream includes a database connection by means of a Database source node this selection lists the functions available from within that database including user defined functions UDFs Operators lists all the operators you can use when building expressions Operators are also available from the buttons in the center of the dialog box All Functions contains a complete list of available CLEM functions 121 Building CLEM Expressions After you have s
331. the new source will replace those in the existing stream Instead of re creating an entire data stream for a new data source you can simply connect to an existing stream The data mapping tool allows you to join together two stream fragments and be sure that all of the essential field names match up properly In essence mapping data results simply in the creation of a new Filter node which matches up the appropriate fields by renaming them There are two equivalent ways to map data Select replacement node This method starts with the node to be replaced First you right click the node to replace then using the Data Mapping gt Select Replacement Node option from the pop up menu select the node with which to replace it 92 Chapter 5 Map to This method starts with the node to be introduced to the stream First right click the node to introduce then using the Data Mapping gt Map To option from the pop up menu select the node to which it should join This method is particularly useful for mapping to a terminal node Note You cannot map to Merge or Append nodes Instead you should simply connect the stream to the Merge node in the normal manner Figure 5 44 Selecting data mapping options gt Connect Discard Fields Disconnect Rename and Annotate Bj New Comment A Cut Copy Node X Delete Load Node 8 Retrieve Node Save Node Store Node Cache es Select Replacement Node Create SuperNode
332. the required nodes you can run the stream by running the data through nodes in the stream There are several ways to run a stream within IBM SPSS Modeler You can m Click Run on the Tools menu m Click one of the Run buttons on the toolbar These buttons allow you to run the entire stream or simply the selected terminal node For more information see the topic BM SPSS Modeler Toolbar in Chapter 3 on p RIJ m Runa single data stream by right clicking a terminal node and clicking Run on the pop up menu a Run part of a data stream by right clicking any non terminal node and clicking Run From Here on the pop up menu Doing so causes only those operations after the selected node to be performed To halt the running of a stream in progress you can click the red Stop button on the toolbar or click Stop Execution on the Tools menu If any stream takes longer than three seconds to run the Execution Feedback dialog box is displayed to indicate the progress Figure 5 31 Execution Feedback dialog box Execution Feedback Please wait executing Node State Time elapsed 00 00 18 M Close dialog once execution is complete 78 Chapter 5 Some nodes have further displays giving additional information about stream execution These are displayed by selecting the corresponding row in the dialog box The first row is selected automatically Working with Models
333. the stream canvas Note Clicking Cut allows you to paste nodes while Delete does not Click Copy Node to make a copy of the node with no connections This can be added to a new or existing stream Click Load Node to open a previously saved node and load its options into the currently selected node Note The nodes must be of identical types Click Retrieve Node to retrieve a node from a connected IBM SPSS Collaboration and Deployment Services Repository 50 Chapter 5 m Click Save Node to save the node s details in a file You can load node details only into another node of the same type m Click Store Node to store the selected node in a connected IBM SPSS Collaboration and Deployment Services Repository m Click Cache to expand the menu with options for caching the selected node Click Data Mapping to expand the menu with options for mapping data to a new source or specifying mandatory fields m Click Create SuperNode to expand the menu with options for creating a SuperNode in the current stream m Click Generate User Input Node to replace the selected node Examples generated by this node will have the same fields as the current node m Click Run From Here to run all terminal nodes downstream from the selected node Caching Options for Nodes To optimize stream running you can set up a cache on any nonterminal node When you set up a cache on a node the cache is filled with the data that passes through th
334. the topic Creating a Subpalette on p 227 Shown Select this field to display the palette tab on the Nodes Palette For more information see the topic Displaying Palette Tabs on the Nodes Palette on p 225 Sub Palettes To select subpalettes for display on a palette tab highlight the required Palette Name and click this button to display the Sub Palettes dialog box For more information see the topic Creating a Subpalette Restore Defaults To completely remove all changes and additions you have made to the palettes and subpalettes and return to the default palette settings click this button on p 227 225 Customizing IBM SPSS Modeler Creating a Palette Tab Figure 12 7 Palette tab creation on the Create Edit Palette dialog box Create Edit Palette Palette name Select nodes to appear in the palette Nodes available Palette Selected Nodes Enterprise View Sources Database Sources Var File Sources Fixed File Sources To create a custom palette tab gt From the Tools menu open the Palette Manager gt To the right of the Shown column click the Add Palette button the Create Edit Palette dialog box is displayed gt Type in a unique Palette name gt In the Nodes available area select the node to be added to the palette tab gt Click the Add Node right arrow button to move the highlighted node to the Selected nodes area Repea
335. timestamp function 135 146 TODAY function 146 toolbar 21 ToolTips annotating nodes 86 trademarks TRAINING_PARTITION function 157 tree based analysis typical applications BO trigonometric functions 139 trim function 141 trim_start function 141 trimend function 41 Type node missing values 102 performance 234 typical applications BO undef function 156 undo 21 Unicode support 248 unicode_char function 41 unicode_value function 141 unlocking IBM SPSS Collaboration and Deployment Services Repository objects 77 unmapping fields P1 260 Index uppertolower function 141 user ID IBM SPSS Modeler Server 13 user options 217 user defined functions UDFs 120 user missing values UTF 8 encoding 56 248 VALIDATION_PARTITION function 157 value_at function I17 T35 values adding to CLEM expressions 122 viewing from a data audit 122 variables version labels IBM SPSS Collaboration and Deployment Services Repository object 183 visual programming 17 warnings 65 s
336. tion of the rem function Function Result Description Returns the remainder of INT divided by INT2 For example INT1 INT1 div INT2 INT2 INT1 rem INT2 Number Details on usage conventions such as how to list items or specify characters in a function are described elsewhere For more information see the topic CLEM Datatypes on p 127 Information Functions Information functions are used to gain insight into the values of a particular field They are typically used to derive flag fields For example you can use the BLANK function to create a flag field indicating records whose values are blank for the selected field Similarly you can check the storage type for a field using any of the storage type functions such as is_string Function Result Description Returns true for all records whose values are blank according to the blank handling rules set in an upstream BLANK FIELD Boolean Type node or source node Types tab Note that this function cannot be called from a script Returns true for all records whose values are undefined Undefined values are system null values displayed in NULL ITEM Boolean IBM SPSS Modeler as null Note that this function cannot be called from a script is_date ITEM Boolean Returns true for all records whose type is a date is_datetime ITEM Boolean pane a all records whose type is a date time is_integer ITEM Boolean R
337. to interpret with a screen reader Please note however that web graphs and distributions can be viewed using the textual summary available from the output window Appendix Unicode Support Unicode Support in IBM SPSS Modeler IBM SPSS Modeler is fully Unicode enabled for both IBM SPSS Modeler and IBM SPSS Modeler Server This makes it possible to exchange data with other applications that support Unicode including multi language databases without any loss of information that might be caused by conversion to or from a locale specific encoding scheme SPSS Modeler stores Unicode data internally and can read and write multi language data stored as Unicode in databases without loss SPSS Modeler can read and write UTF 8 encoded text files Text file import and export will default to the locale encoding but support UTF 8 as an alternative This setting can be specified in the file import and export nodes or the default encoding can be changed in the stream properties dialog box For more information see the topic Setting general options for streams in Chapter 5 on p 55 Statistics SAS and text data files stored in the locale encoding will be converted to UTF 8 on import and back again on export When writing to any file if there are Unicode characters that do not exist in the locale character set they will be substituted and a warning will be displayed This should occur only where the data has been imported from a data so
338. ton and press Enter to close the dialog box Ctrl Right Arrow Gives focus to the second node a Derive node Enter Opens the Derive node dialog box Tab through to select fields and specify derive conditions Press Ctrl Tab to navigate to the OK button and press Enter to close the dialog box Ctrl Right Arrow Gives focus to the third node a Histogram node Enter Opens the Histogram node dialog box Tab through to select fields and specify graph options For drop down lists press Down Arrow to open the list and to highlight a list item then press Enter to select the list item Tab through to the OK button and press Enter to close the dialog box At this point you can add additional nodes or run the current stream Keep in mind the following tips when you are building streams m When manually connecting nodes use F2 to create the start point of a connection tab to move to the end point then use Shift Spacebar to finalize the connection 245 Accessibility in IBM SPSS Modeler m Use F3 to destroy all connections for a selected node in the canvas m Once you have created a stream use Ctrl E to run the current stream A complete list of shortcut keys is available For more information see the topic Shortcuts for avigating the Main Window on p 238 Using a Screen Reader A number of screen readers are available on the market IBM SPSS Modeler is configured to support JAWS for Windows using t
339. u exit IBM SPSS Modeler with multiple unsaved objects such as streams projects or model nuggets you will be prompted to save before completely closing the software If you choose to save items a dialog box will open with options for saving each object Figure 5 41 Saving multiple objects H Save Files Save the following individual files E Z Al Contents ay Streams iModels Palette ao Unsaved Output Histogram of Score _ gains i profit gt Simply select the check boxes for the objects that you want to save gt Click OK to save each object in the required location You will then be prompted with a standard Save dialog box for each object After you have finished saving the application will close as originally instructed Saving Output Tables graphs and reports generated from IBM SPSS Modeler output nodes can be saved in output object cou format gt When viewing the output you want to save on the output window menus click File gt Save gt Specify a name and location for the output file gt Optionally select Add file to project in the Save dialog box to include the file in the current project For more information see the topic Introduction to Projects in Chapter 11 on p 200 Alternatively you can right click any output object listed in the managers pane and select Save from the pop up menu 90 Chapter 5 Encrypting and Decrypting
340. uivalent sum_n FIELDS_BETWEEN card1bal card3bal Alternatively to count the number of null values across all fields beginning with card count_nulls FIELDS_MATCHING card For more information see the topic Special Fields in Chapter 8 on p 157 117 Building CLEM Expressions Working with Multiple Response Data A number of comparison functions can be used to analyze multiple response data including m value_at m first_index last_index m first non_null last_non_null m first_non_null_index last_non_null_index m min_index max_index For example suppose a multiple response question asked for the first second and third most important reasons for deciding on a particular purchase for example price personal recommendation review local supplier other In this case you might determine the importance of price by deriving the index of the field in which it was first included first_index price Reason1 Reason2 Reason3 Similarly suppose you have asked customers to rank three cars in order of likelihood to purchase and coded the responses in three separate fields as follows customer id carl car2 car3 101 1 3 2 102 3 2 1 103 2 3 1 In this case you could determine the index of the field for the car they like most ranked 1 or the lowest rank using the min_index function min_index car1 car2 car3 For more inform
341. unction 141 ismidstring function 41 isnumbercode function 41 isstartstring function 14 issubstring function I 41 issubstring_ count function 141 issubstring_lim function 41 isuppercode function 141 Java 247 JAWS 236 245 247 K Means node large sets 57 performance 234 keyboard shortcuts 238 240 242 keywords annotating nodes 86 knowledge discovery 29 Kohonen node large sets 57 performance 234 labels displaying 57 value 97 variable 197 Index labels IBM SPSS Collaboration and Deployment Services Repository object 183 language options 215 last_index function 117 135 LAST_NON_BLANK function 152 LAST_NON_BLANK function 150 152 156 last_non_null function 117 135 135 last_non_null_index function legal notices 249 length function 141 less than operator 135 linear regression export as PMML 222 listing all comments for a stre lists 27 129 loading nodes PO states 90 locale options 215 locchar function 141 locchar_back function locking IBM SPSS Collabora Services Repository objects locking nodes 53 log files displaying generated SQL log function 138 log10 function 138
342. urce that supports Unicode a database or UTF 8 text file and that contains characters from a different locale or from multiple locales or character sets IBM SPSS Modeler Solution Publisher images are UTF 8 encoded and are truly portable between platforms and locales About Unicode The goal of the Unicode standard is to provide a consistent way to encode multilingual text so that it can be easily shared across borders locales and applications The Unicode Standard now at version 4 0 1 defines a character set that is a superset of all of the character sets in common use in the world today and assigns to each character a unique name and code point The characters and their code points are identical to those of the Universal Character Set UCS defined by ISO 10646 For more information see the Unicode Home Page http www unicode org Copyright IBM Corporation 1994 2012 248 Appendix Notices This information was developed for products and services offered worldwide IBM may not offer the products services or features discussed in this document in other countries Consult your local IBM representative for information on the products and services currently available in your area Any reference to an IBM product program or service is not intended to state or imply that only that IBM product program or service may be used Any functionally equivalent product program or service t
343. use SQL pushback may generate different results where trailing spaces exist Function Result Description allbutfirst N STRING String Returns a string which is STRING with the first N characters removed allbutlast N STRING String Returns a string which is STRING with the last characters removed alphabefore STRING1 STRING2 Boolean Used to check the alphabetical ordering of strings Returns true if STRINGI precedes STRING2 endstring LENGTH STRING String Extracts the last N characters from the specified string If the string length is less than or equal to the specified length then it is unchanged hasendstring STRING SUBSTRING Integer This function is the same as isendstring SUBSTRING STRING hasmidstring STRING SUBSTRING Integer This function is the same as ismidstring SUBSTRING STRING embedded substring hasstartstring STRING SUBSTRING Integer This function is the same as isstartstring SUBSTRING STRING hassubstring STRING N SUBSTRING Integer This function is the same as issubstring SUBSTRING N STRING where N defaults to 1 count_substring STRING SUBSTRING Integer Returns the number of times the specified substring occurs within the string For example count_substring foooo txt oo returns 3 hassubstring STRING SUBSTRING Integer This function is the same as issubstring SUB
344. ut object from the current stream as a cou file in the repository from where it can be accessed by other users To store an output object gt Click the object on the Outputs tab of the managers pane in SPSS Modeler and on the main menu click File gt Outputs gt Store Output gt Alternatively right click an object in the Outputs tab and click Store gt Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator gt Inthe Repository Store dialog box choose the folder where you want to store the object specify any other information you want to record and click the Store button For more information see the topic Setting Object Properties on p 164 172 Chapter 9 Storing Models and Model Palettes You can store an individual model as a gm file in the repository from where it can be accessed by other users You can also store the complete contents of the Models palette as a gen file in the repository Storing a model gt Click the object on the Models palette in SPSS Modeler and on the main menu click File gt Models gt Store Model gt Alternatively right click an object in the Models palette and click Store Model gt Continue from Completing the storage procedure
345. utputs and Models tabs in the managers pane at the top right of the display when new items are generated Select New Model or New Output from the list to specify the behavior of the corresponding tab The following options are available for New Model Add model to stream If selected default adds a new model to the stream as well as to the Models tab as soon as the model is built In the stream the model is shown with a link to the modeling node from which the model was created If you uncheck this box the model is added only to the Models tab Replace previous model If selected default overwrites an existing model from this stream in the Models tab and on the stream canvas If this box is unchecked the model is added to the existing models on the tab and the canvas Note that this setting is overridden by the model replacement setting on a model link The following options are available for New Output Warn when outputs exceed n Select whether to display a warning when the number of items on the Outputs tab exceeds a prespecified quantity The default quantity is 20 however you can change this if needed The following options are available in all cases Select tab Choose whether to switch to the Outputs or Models tab when the corresponding object is generated while the stream runs m Select Always to switch to the corresponding tab in the managers pane m Select If generated by current stream to switch to the correspond
346. utton The Regression submenu now supports Partial Least Squares regression and there is a new Forecasting submenu with the following options Spectral Analysis Sequence Charts Autocorrelations and Cross correlations For more information see the SPSS Statistics documentation The Syntax tab of the Statistics Output node also has a new option to generate a Statistics File source node for importing the data that results from running a stream containing the node This is useful where a procedure writes fields such as scores to the active dataset in addition to displaying output as these fields would otherwise not be visible Non root user on UNIX servers If you have SPSS Modeler Server installed on a UNIX server you can now install configure and start and stop SPSS Modeler Server as a non root user without the need for a private password database Deployed streams can now access IBM SPSS Collaboration and Deployment Services model management features When a stream is deployed to IBM SPSS Collaboration and Deployment Services as a stream it can now use the same model management features as it could if deployed as a scenario These features include evaluation refresh score and champion challenger Improved method of changing ODBC connection for SPSS Modeler stream and scenario job steps For stream and scenario job steps in IBM SPSS Collaboration and Deployment Services changes to an ODBC connection and related logon credentials apply to a
347. valent agreement between us Any performance data contained herein was determined in a controlled environment Therefore the results obtained in other operating environments may vary significantly Some measurements may have been made on development level systems and there is no guarantee that these measurements will be the same on generally available systems Furthermore some measurements may have been estimated through extrapolation Actual results may vary Users of this document should verify the applicable data for their specific environment Information concerning non IBM products was obtained from the suppliers of those products their published announcements or other publicly available sources IBM has not tested those products and cannot confirm the accuracy of performance compatibility or any other claims related to non IBM products Questions on the capabilities of non IBM products should be addressed to the suppliers of those products All statements regarding IBM s future direction or intent are subject to change or withdrawal without notice and represent goals and objectives only This information contains examples of data and reports used in daily business operations To illustrate them as completely as possible the examples include the names of individuals companies brands and products All of these names are fictitious and any similarity to the names and addresses used by an actual business enterprise is entirely coincident
348. values are field sex type flag sex m f etc Ctrl D For tables reads the short Description of the selected area For example Selection is one row by six columns Ctrl Alt D For tables provides the long Description of the selected area For example Selection is one row by six columns Selected columns are Field Type Missing Selected row is 1 Ctrl T For tables provides a short description of the selected columns For example Fields Type Missing Ctrl Alt T For tables provides a long description of the selected columns For example Selected columns are Fields Type Missing Ctrl R For tables provides the number of Records in the table Ctrl Alt R For tables provides the number of Records in the table as well as column names Ctrl I For tables reads the cell Information or contents for the cell that has focus Ctrl Alt I For tables reads the long description of cell Information column name and contents of the cell for the cell that has focus Ctrl G For tables provides short General selection information Ctrl Alt G For tables provides long General selection information Ctrl Q For tables provides a Quick toggle of the table cells Ctrl Q reads long descriptions such as Sex Female as you move through the table using the arrow keys Selecting Ctrl Q again will toggle to short descriptions cell contents 242 Appendix A Shortcuts for Comments When workin
349. values available for the stream mailshot5 MEAN sum max 42 093 12628 27250430 8175129 020 18 5014 210 67 63130 100 13091 474 Globals available Available globals are listed in this table You cannot edit global values here but you can clear all global values for a stream using the Clear All Values button to the right of the table 73 Building Streams Searching for Nodes in a Stream You can search for nodes in a stream by specifying a number of search criteria such as node name category and identifier This feature can be especially useful for complex streams containing a large number of nodes To Search for Nodes in a Stream gt On the File menu click Stream Properties or select the stream from the Streams tab in the managers pane right click and then click Stream Properties on the pop up menu gt Click the Search tab Alternatively on the Tools menu click Stream Properties gt Search Figure 5 29 Searching for nodes in a stream IM Node label contains E Node category Source Node Keywords include Annotation contains Generates field called ID equals N Search in SuperNodes Node Type Location 2 DRUGIn Var File W druglearn Discard Fields Filter druglearn Na_to_K Derive a druglearn amp Drug Neural Net druglearn Define Types Type lt druglearn Drug c5 0 E druglearn You can specify more t
350. vices Enterprise View Driver must be installed on each computer used to modify or run the stream For Windows simply install the driver on the computer where SPSS Modeler or SPSS Modeler Server is installed and no further configuration of the driver is needed On UNIX a reference to the pev sh script must be added to the startup script Contact your local administrator for details on installing the IBM SPSS Collaboration and Deployment Services Enterprise View Driver 161 Using IBM SPSS Modeler with a Repository Other Deployment Options While IBM SPSS Collaboration and Deployment Services offers the most extensive features for managing enterprise content a number of other mechanisms for deploying or exporting streams are also available including m Export the stream and model for later use with IBM SPSS Modeler Solution Publisher Runtime m Export one or more models in PMML an XML based format for encoding model information For more information see the topic Importing and Exporting Models as PMML in Chapter 10 on p 96 Connecting to the Repository gt To connect to the repository on the IBM SPSS Modeler main menu click Tools gt Repository gt Options gt Specify login options as required Settings are specific to each site or installation For specific port and other login details contact your local system administrator Note A separate license is required to access an IBM S
351. vices Repository credentials Repository Credentials User ID admin a WIE Password Provider _ Remember repository and user ID User ID and password Specify a valid user name and password for logging on If necessary contact your local administrator for more information Provider Choose a security provider for authentication The repository can be configured to use different security providers if necessary contact your local administrator for more information Remember repository and user ID Saves the current settings as the default so that you do not have to reenter them each time you want to connect Browsing the Repository Contents The repository allows you to browse stored content in a manner similar to Windows Explorer you can also browse versions of each stored object To open the IBM SPSS Collaboration and Deployment Services Repository window on the SPSS Modeler menus click Tools gt Repository gt Explore Specify connection settings to the repository if necessary For more information see the topic Connecting to the Repository on p L61 For specific port password and other connection details contact your local system administrator 163 Using IBM SPSS Modeler with a Repository Figure 9 4 Browsing the IBM SPSS Collaboration and Deployment Services Repository contents Baie Size Vverson_ _ Labels_ Last Modified author 13 KB 0
352. wer POWER rem Used between two integers INT1 rem INT2 Returns the remainder INT1 INT1 div INT2 INT2 div Used between two integers INT1 div INT2 Performs integer division Operator Precedence Precedences determine the parsing of complex expressions especially unbracketed expressions with more than one infix operator For example 3 4 5 parses as 3 4 5 rather than 3 4 5 because the relative precedences dictate that is to be parsed before Every operator in the CLEM language has a precedence value associated with it the lower this value the more important it is on the parsing list meaning that it will be processed sooner than other operators with higher precedence values 133 Functions Reference CLEM Language Reference The following CLEM functions are available for working with data in IBM SPSS Modeler You can enter these functions as code in a variety of dialog boxes such as Derive and Set To Flag nodes or you can use the Expression Builder to create valid CLEM expressions without memorizing function lists or field names Function Type Description Information Used to gain insight into field values For example the function is_string returns true for all records whose type is a string Conversion Used to construct new fields or convert storage type For example the function to_timestamp converts the selected field to a timesta
353. ys used in SPSS Modeler conflict with standard Windows shortcut keys These old shortcuts are supported with the addition of the Alt key For example Ctrl Alt C can be used to toggle the cache on and off Table 3 1 Supported shortcut keys Shortcut Function Key Ctrl A Select all Ctrl X Cut Ctrl N New stream Ctrl O Open stream Ctrl P Print Ctrl C Copy Ctrl V Paste Ctrl Z Undo Ctrl Q Select all nodes downstream of the selected node Ctrl W Deselect all downstream nodes toggles with Ctrl Q Ctrl E Run from selected node Ctrl S Save current stream Alt Arrow Move selected nodes on the stream canvas in the direction keys of the arrow used Shift F10 Open the pop up menu for the selected node 27 IBM SPSS Modeler Overview Table 3 2 Supported shortcuts for old hot keys Shortcut Function Key Ctrl Alt D Duplicate node Ctrl Alt L Load node Ctrl Alt R Rename node Ctrl Alt U_ Create User Input node Ctrl Alt C Toggle cache on off Ctrl Alt F Flush cache Ctrl Alt X Expand SuperNode Ctrl Alt Z Zoom in zoom out Delete Delete node or connection Printing The following objects can be printed in IBM SPSS Modeler Stream diagrams Graphs Tables Reports from the Report node and Project Reports Scripts from the stream properties Standalone Script or SuperNode script dialog boxes
354. z5 Optimization Minimum Stream canvas height Logging and Status Stream scroll rate Leyot O Icon name maximum Icon size Grid cell size Generated icon placement Minimum stream canvas width Specify the minimum width of the stream canvas in pixels Minimum stream canvas height Specify the minimum height of the stream canvas in pixels 65 Building Streams Stream scroll rate Specify the scrolling rate for the stream canvas to control how quickly the stream canvas pane scrolls when a node is being dragged from one place to another on the canvas Higher numbers specify a faster scroll rate Icon name maximum Specify a limit in characters for the names of nodes on the stream canvas Icon size Select an option to scale the entire stream view to one of a number of sizes between 8 and 200 of the standard icon size Grid cell size Select a grid cell size from the list This number is used for aligning nodes on the stream canvas using an invisible grid The default grid cell size is 0 25 Snap to Grid Select to align icons to an invisible grid pattern selected by default Generated icon placement Choose where on the canvas to place icons for nodes generated from model nuggets Default is top left Save As Default The options specified apply only to the current stream Click this button to set these options as the default for all streams Viewing Stream Operation Messages Messages regarding stream operati

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