applyglmmnode properties

Last updated: Jan 18, 2024

You can use GLMM modeling nodes to generate a GLMM model nugget. The scripting name of this model nugget is applyglmmnode. For more information on scripting the modeling node itself, see glmmnode properties.

Table 1. applyglmmnode properties
`applyglmmnode` Properties	Values	Property description
`confidence`	`onProbability` `onIncrease`	Basis for computing scoring confidence value: highest predicted probability, or difference between highest and second highest predicted probabilities.
`score_category_probabilities`	flag	If set to `True`, produces the predicted probabilities for categorical targets. A field is created for each category. Default is `False`.
`max_categories`	integer	Maximum number of categories for which to predict probabilities. Used only if `score_category_probabilities` is `True`.
`score_propensity`	flag	If set to `True`, produces raw propensity scores (likelihood of "True" outcome) for models with flag targets. If partitions are in effect, also produces adjusted propensity scores based on the testing partition. Default is `False`.
`enable_sql_generation`	`false` `true` `native`	Used to set SQL generation options during flow execution. The options are to push back to the database, or to score within SPSS Modeler.