The GENESELECT Procedure (Experimental)

SCORE Statement

SCORE <options> ;

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.

DATA=SAS-data-set: names the input data set. If the DATA= option is absent, the procedure uses the data.
PREDICTION | NOPREDICTION: indicates whether prediction variables, such as P_*, should be generated. The default is PREDICTION, requesting prediction variables.
OUT=SAS-data-set: 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 $\text{[math]}$ convention. Specify OUT=_NULL_ to avoid creating a scored data set.
OUTFIT=SAS-data-set: names the output data set to contain the fit statistics.
ROLE=TRAIN | VALID | TEST | SCORE: 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.

Note: This procedure is experimental.