IBM SPSS Modeler 18.1.1 Python Scripting and Automation Guide

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IBM SPSS Modeler 18.1.1 Python Scripting and Automation Guide IBM SPSS Modeler 18.1.1 Python Scripting and Automation Guide IBM Note Before you use this information and the product it supports, read the information in “Notices” on page 359. Product Information This edition applies to version 18, release 1, modification 1 of IBM SPSS Modeler and to all subsequent releases and modifications until otherwise indicated in new editions. Contents Chapter 1. Scripting and the Scripting Creating nodes and modifying streams ..... 30 Language .............. 1 Creating nodes ............ 30 Scripting overview ............ 1 Linking and unlinking nodes ....... 31 Types of Scripts ............. 1 Importing, replacing, and deleting nodes ... 32 Stream Scripts .............. 1 Traversing through nodes in a stream .... 33 Stream script example: Training a neural net... 3 Clearing, or removing, items ........ 33 Jython code size limits .......... 3 Getting information about nodes ....... 33 Standalone Scripts ............ 4 Standalone script example: Saving and loading a Chapter 4. The Scripting API ..... 37 model ............... 4 Introduction to the Scripting API ....... 37 Standalone script example: Generating a Feature Example 1: searching for nodes using a custom filter 37 Selection model ............ 4 Example 2: allowing users to obtain directory or file SuperNode Scripts ............ 5 information based on their privileges ...... 37 SuperNode Script Example ........ 6 Metadata: Information about data ....... 38 Looping and conditional execution in streams ... 6 Accessing Generated Objects ........ 40 Looping in streams ........... 7 Handling Errors ............. 42 Conditional execution in streams ...... 10 Stream, Session, and SuperNode Parameters ... 42 Executing and interrupting scripts ....... 11 Global Values.............. 46 Find and Replace ............ 12 Working with Multiple Streams: Standalone Scripts 47 Chapter 2. The Scripting Language .. 15 Chapter 5. Scripting tips ....... 49 Scripting language overview......... 15 Modifying stream execution ......... 49 Python and Jython ............ 15 Looping through nodes .......... 49 Python Scripting............. 16 Accessing Objects in the IBM SPSS Collaboration Operations ............. 16 and Deployment Services Repository ...... 49 Lists ................ 16 Generating an encoded password ....... 52 Strings ............... 17 Script checking ............. 52 Remarks .............. 18 Scripting from the command line ....... 52 Statement Syntax ........... 18 Compatibility with previous releases ...... 52 Identifiers .............. 19 Accessing Stream Execution Results ...... 53 Blocks of Code ............ 19 Table content model .......... 53 Passing Arguments to a Script ....... 19 XML Content Model .......... 55 Examples .............. 20 JSON Content Model .......... 56 Mathematical Methods ......... 21 Column statistics content model and pairwise Using Non-ASCII characters ........ 22 statistics content model ......... 58 Object-Oriented Programming ........ 23 Defining a Class ............ 23 Chapter 6. Command Line Arguments 61 Creating a Class Instance ......... 24 Invoking the Software ........... 61 Adding Attributes to a Class Instance .... 24 Using command line arguments ....... 61 Defining Class Attributes and Methods .... 24 System arguments ........... 62 Hidden Variables ........... 24 Parameter arguments .......... 63 Inheritance ............. 25 Server connection arguments ....... 64 IBM SPSS Collaboration and Deployment Chapter 3. Scripting in IBM SPSS Services Repository Connection Arguments... 65 Modeler .............. 27 IBM SPSS Analytic Server connection arguments 65 Types of scripts ............. 27 Combining Multiple Arguments ...... 65 Streams, SuperNode streams, and diagrams ... 27 Streams............... 27 Chapter 7. Properties Reference .... 67 SuperNode streams........... 27 Properties reference overview ........ 67 Diagrams .............. 27 Syntax for properties .......... 67 Executing a stream ............ 27 Node and stream property examples ..... 68 The scripting context ........... 28 Node properties overview ......... 69 Referencing existing nodes ......... 28 Common Node Properties ........ 69 Finding nodes ............ 29 Setting properties ........... 29 iii Chapter 8. Stream properties ..... 71 transposenode properties ......... 148 typenode properties ........... 150 Chapter 9. Source Node Properties .. 75 Source node common properties ....... 75 Chapter 12. Graph Node Properties 155 asimport Properties............ 79 Graph node common properties ....... 155 cognosimport Node Properties ........ 80 collectionnode Properties ......... 156 databasenode properties .......... 82 distributionnode Properties......... 157 datacollectionimportnode Properties ...... 83 evaluationnode Properties ......... 157 excelimportnode Properties ......... 86 graphboardnode Properties......... 159 extensionimportnode properties ....... 87 histogramnode Properties ......... 161 fixedfilenode Properties .......... 89 mapvisualization properties ........ 162 gsdata_import Node Properties ........ 92 multiplotnode Properties ......... 166 sasimportnode Properties.......... 92 plotnode Properties ........... 167 simgennode properties .......... 93 timeplotnode Properties .......... 169 statisticsimportnode Properties ........ 94 eplotnode Properties ........... 170 tm1odataimport Node Properties ....... 95 tsnenode Properties ........... 171 tm1import Node Properties (deprecated) .... 95 webnode Properties ........... 173 twcimport node properties ......... 96 userinputnode properties .......... 97 Chapter 13. Modeling Node Properties 175 variablefilenode Properties ......... 98 Common Modeling Node Properties ..... 175 xmlimportnode Properties ......... 101 anomalydetectionnode properties....... 175 dataviewimport Properties ......... 101 apriorinode properties .......... 177 associationrulesnode properties ....... 178 Chapter 10. Record Operations Node autoclassifiernode properties ........ 180 Properties ............. 103 Setting Algorithm Properties ....... 182 appendnode properties .......... 103 autoclusternode properties ......... 182 aggregatenode properties ......... 103 autonumericnode properties ........ 184 balancenode properties .......... 104 bayesnetnode properties.......... 185 cplexoptnode properties .......... 105 c50node properties ........... 187 derive_stbnode properties ......... 107 carmanode properties .......... 188 distinctnode properties .......... 109 cartnode properties ........... 189 extensionprocessnode properties ....... 111 chaidnode properties ........... 191 mergenode properties .......... 112 coxregnode properties .......... 193 rfmaggregatenode properties ........ 114 decisionlistnode properties ......... 195 samplenode properties .......... 116 discriminantnode properties ........ 196 selectnode properties ........... 117 extensionmodelnode properties ....... 198 sortnode properties ........... 118 factornode properties ........... 200 spacetimeboxes properties ......... 118 featureselectionnode properties ....... 202 streamingtimeseries Properties........ 120 genlinnode properties .......... 203 glmmnode properties........... 207 Chapter 11. Field Operations Node gle properties ............. 210 kmeansnode properties .......... 214 Properties ............. 127 kmeansasnode properties ......... 215 anonymizenode properties ......... 127 knnnode properties ........... 216 autodataprepnode properties ........ 128 kohonennode properties .......... 217 astimeintervalsnode properties ....... 130 linearnode properties ........... 218 binningnode properties .......... 131 linearasnode properties .......... 220 derivenode properties .......... 133 logregnode properties .......... 221 ensemblenode properties ......... 135 lsvmnode properties ........... 225 fillernode properties ........... 136 neuralnetnode properties ......... 226 filternode properties ........... 137 neuralnetworknode properties........ 228 historynode properties .......... 138 questnode properties ........... 230 partitionnode properties .......... 139 randomtrees properties .......... 231 reclassifynode properties ......... 140 regressionnode properties ......... 233 reordernode properties .......... 140 sequencenode properties ......... 235 reprojectnode properties .......... 141 slrmnode properties ........... 236 restructurenode properties ......... 141 statisticsmodelnode properties........ 237 rfmanalysisnode properties ......... 142 stpnode properties ........... 237 settoflagnode properties .......... 143 svmnode properties ........... 241 statisticstransformnode properties ...... 144 tcmnode Properties ........... 242 timeintervalsnode properties (deprecated) .... 144 iv IBM SPSS Modeler 18.1.1 Python Scripting and Automation Guide ts properties .............. 246 Oracle Model Nugget Properties ...... 282 treeas properties ............ 252 Node Properties for IBM Netezza Analytics twostepnode Properties .......... 253 Modeling............... 283 twostepAS Properties........... 254 Netezza Modeling Node Properties ..... 283 Netezza Model Nugget Properties ..... 293 Chapter 14. Model nugget node properties ............. 257 Chapter 16. Output node properties 295 applyanomalydetectionnode Properties ..... 257 analysisnode properties .......... 295 applyapriorinode Properties ........ 257 dataauditnode properties ......... 296 applyassociationrulesnode Properties ..... 258 extensionoutputnode properties ....... 297 applyautoclassifiernode Properties ...... 258 matrixnode properties .......... 299 applyautoclusternode
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