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Machine Learning Procedures
 

GPCLASS Procedure

PROC GPCLASS Statement

  • PROC GPCLASS <options>;

The PROC GPCLASS statement invokes the procedure. Table 1 summarizes the options available in this statement.

Table 1: PROC GPCLASS Statement Options

Option Description
Input and Output Data Set Options
DATA= Specifies the input training data table
ID= Specifies the IDs of observations in the data table
TESTDATA= Specifies the input testing data table
Gaussian Process Option
LINK= Specifies the likelihood function of the Gaussian process
Performance Options
NTHREADS= Specifies the number of threads for the computation
SEED= Specifies the seed for the computation


You can specify the following options:

DATA=libref.data-table

names the input data table for PROC GPCLASS to use. The default is the most recently created data table. libref.data-table is a two-level name, where

libref

refers to a collection of information that is defined in the LIBNAME statement and includes the library, which includes a path to the data, and a session identifier, which defaults to the active session but which can be explicitly defined in the LIBNAME statement. For more information about libref, see the section Using CAS Sessions and CAS Engine Librefs.

data-table

specifies the name of the input data table.

ID=variable

specifies the variable that contains IDs of the observations in the input data table. This option specifies a column in the input data table to contain the input observations IDs.

LINK=keyword

specifies the link function to be used in the Gaussian process classification. In this method of classification, the link function is a sigmoid type of function that maps from the latent Gaussian process to a real number between 0 and 1 (that is, the predicted class probability). PROC GPCLASS currently supports only the logit function. For more information, see the section Link Function.

NTHREADS=number-of-threads

specifies the number of threads to use in the computation. The default value is the number of CPUs available in the machine.

SEED=number

specifies an integer to be used to start the pseudorandom number generator. If you do not specify a seed or if you specify a value less than or equal to 0, the seed is generated by reading the time of day from the computer’s clock.

TESTDATA=libref.data-table

names the input data table for PROC GPCLASS to use for testing.

As a supervised machine learning procedure, PROC GPCLASS takes its input data in two parts: the training data table as specified by the DATA= option and the test testing data table as specified by the TESTDATA= option. The procedure first performs the training task of the Gaussian process classification, and then it performs the testing process in which the predicted class labels and probabilities are generated from the data in the testing data table.

Last updated: September 04, 2026