Specifies the name of the eigenvector output table
You can specify the following options:
CENTER
centers the observations by the mean of each column.
CENTROIDS=CAS-libref.data-table
specifies the name of the output table for the centroids that are generated by clustering. This table is generated if METHOD=APPROXIMATE.
CAS-libref.data-table is a two-level name, where CAS-libref refers to the caslib and session identifier, and data-table specifies the name of the output data table. For more information about this two-level name, see the DATA= option and the section Using CAS Sessions and CAS Engine Librefs.
DATA=CAS-libref.data-table
names the input data table for PROC KPCA to use. The default is the most recently created data table. CAS-libref.data-table is a two-level name, where
CAS-libref
refers to a collection of information that is defined in the LIBNAME statement and includes the caslib, 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 CAS-libref, see the section Using CAS Sessions and CAS Engine Librefs.
data-table
specifies the name of the input data table.
EIGENVAL=CAS-libref.data-table
specifies the name of the output table that contains the eigenvalues.
CAS-libref.data-table is a two-level name, where CAS-libref refers to the caslib and session identifier, and data-table specifies the name of the output data table. For more information about this two-level name, see the DATA= option and the section Using CAS Sessions and CAS Engine Librefs.
EIGENVEC=CAS-libref.data-table
specifies the name of the output table that contains the eigenvectors.
CAS-libref.data-table is a two-level name, where CAS-libref refers to the caslib and session identifier, and data-table specifies the name of the output data table. For more information about this two-level name, see the DATA= option and the section Using CAS Sessions and CAS Engine Librefs.
METHOD=APPROXIMATE | EXACT
specifies the method to use in performing KPCA. You can specify the following values:
APPROXIMATE
uses the low-rank approximation method.
EXACT
uses the exact method.
By default, METHOD=APPROXIMATE.
NTHREADS=number-of-threads
specifies the number of threads per computation node. The default value is the lesser of 16 and the number of threads available per computation node.
RANKTHRESHOLD=number
specifies the value of epsilon for determining the rank of the kernel matrix. The default number is .
SCALE
scales the observations by the standard deviation of each column. If a constant variable exists (where all observations have the same value), the observations of this column are not scaled.