GenLin Model Nugget Settings

The Settings tab for a GenLin model nugget allows you to obtain propensity scores when scoring the model, and also for SQL generation during model scoring. This tab is available for models with flag targets only, and only after the model nugget has been added to a stream.

Calculate raw propensity scores. For models with a flag target (which return a yes or no prediction), you can request propensity scores that indicate the likelihood of the true outcome specified for the target field. These are in addition to other prediction and confidence values that may be generated during scoring.

Calculate adjusted propensity scores. Raw propensity scores are based only on the training data and may be overly optimistic due to the tendency of many models to overfit this data. Adjusted propensities attempt to compensate by evaluating model performance against a test or validation partition. This option requires that a partition field be defined in the stream and adjusted propensity scores be enabled in the modeling node before generating the model.

Generate SQL for this model When using data from a database, SQL code can be pushed back to the database for execution, providing superior performance for many operations.

Select one of the following options to specify how SQL generation is performed.

• Default: Score using Server Scoring Adapter (if installed) otherwise in process If connected to a database with a scoring adapter installed, generates SQL using the scoring adapter and associated user defined functions (UDF) and scores your model within the database. When no scoring adapter is available, this option fetches your data back from the database and scores it in SPSS® Modeler.
• Score outside of the Database If selected, this option fetches your data back from the database and scores it in SPSS Modeler.