PARTITION <option>;
The PARTITION statement specifies how observations in the input data set are logically partitioned into disjoint subsets for model training, validation, and testing. Either you can designate a variable in the input data set and a set of formatted values of that variable to determine the role of each observation, or you can specify proportions to use for random assignment of observations for each role.
An alternative to using a PARTITION statement is to provide a variable named _ROLE_ in the input data set to define roles of observations in the input data. For more information about the _ROLE_ variable, see the description of the OUTDESIGN= option and see the section OUTPUT Statement. The QUANTSELECT procedure ignores all observations whose _ROLE_ values are not equal to TRAIN, TEST, or VALIDATE. If you specify the PARTITION statement, then the _ROLE_ variable in the input data set (if it exists) is ignored. If you do not use a PARTITION statement and the input data do not contain a variable named _ROLE_, then all observations in the input data set are assigned to model training.
You can specify either (but not both) of the following options: