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Partitioning columns result in building a virtual model for each unique partition.
Because the virtual model uses data only from a specific partition, it can potentially predict cases more accurately than if you did not select a partition.
In addition to selecting attributes, you can specify partitioning expressions. Partitioning expressions are concatenated and the result expression is the same for all predictive functions.
Select one or more attributes from the Available Attributes list to serve as partitions.
Move the selected columns to the Selected list.
Click OK.
The selected attributes are moved to the Partition list.
Optionally, you can Add Partitioning Expressions