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
onProbabilityonIncrease
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
falsetruenative
Used to set SQL generation options during flow execution. The options are to push back to the
database, or to score within SPSS Modeler.
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