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You can use the 'sum', 'mean', 'max', 'min', 'range', or 'nMiss' parameters to specify the variables for which you want to compute these statistics. The results are added as new variables to the output table.
Specifies the weight variable.
The nClassLevelsPrint parameter limits the display of class levels. Setting its value to 0 suppresses all levels. The minimum value is 0.
Trains a gradient boosting tree. This action requires a SAS Visual Data Mining and Machine Learning license.
specifies that graph partitioning is to be used- the layout algorithms (which depend on layout=, and parallel=) become sub-algorithms. More costly timewise, but the layout is often better quality. Alias: gp. Default: FALSE.