Database modeling node properties

IBM® SPSS® Modeler supports integration with data mining and modeling tools available from database vendors, including Microsoft SQL Server Analysis Services, Oracle Data Mining, and IBM Netezza® Analytics. You can build and score models using native database algorithms, all from within the IBM SPSS Modeler application. Database models can also be created and manipulated through scripting using the properties described in this section.

For example, the following script excerpt illustrates the creation of a Microsoft Decision Trees model by using the IBM SPSS Modeler scripting interface:

stream = modeler.script.stream()
msbuilder = stream.createAt("mstreenode", "MSBuilder", 200, 200)

msbuilder.setPropertyValue("analysis_server_name", 'localhost')
msbuilder.setPropertyValue("analysis_database_name", 'TESTDB')
msbuilder.setPropertyValue("mode", 'Expert')
msbuilder.setPropertyValue("datasource", 'LocalServer')
msbuilder.setPropertyValue("target", 'Drug')
msbuilder.setPropertyValue("inputs", ['Age', 'Sex'])
msbuilder.setPropertyValue("unique_field", 'IDX')
msbuilder.setPropertyValue("custom_fields", True)
msbuilder.setPropertyValue("model_name", 'MSDRUG')

typenode = stream.findByType("type", None)
stream.link(typenode, msbuilder)
results = []
msbuilder.run(results)
msapplier = stream.createModelApplierAt(results[0], "Drug", 200, 300)
tablenode = stream.createAt("table", "Results", 300, 300)
stream.linkBetween(msapplier, typenode, tablenode)
msapplier.setPropertyValue("sql_generate", True)
tablenode.run([])