The SCORE statement reads a data set containing the input variables used in the model and then outputs a data set containing
the original variables plus new variables to contain predictions, residuals, decisions, and leaf assignments. The SCORE statement
can be repeated.
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DATA=SAS-data-set
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names the input data set. If the DATA= option is absent, the procedure uses the data.
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PREDICTION | NOPREDICTION
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indicates whether prediction variables, such as P_*
, should be generated. The default is PREDICTION, requesting prediction variables.
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OUT=SAS-data-set
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names the output data set to contain the scored data. If the OUT= option is absent, the procedure creates a data set name
by using the DATA convention. Specify OUT=_NULL_ to avoid creating a scored data set.
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OUTFIT=SAS-data-set
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names the output data set to contain the fit statistics.
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ROLE=TRAIN | VALID | TEST | SCORE
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specifies the role of the input data set and determines the fit statistics to compute. For ROLE=TRAIN, VALID, or TEST, observations
without a trait value are ignored.
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