Last updated: Feb 11, 2025
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.
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. |