classify

Description: Classify a set of unlabeled vectors using a trained support vector machine.

Usage: classify [options] -train <filename> -weights <filename> -test <filename> -label <filename>

Input:

Note that, if the given weights file was trained on an externally defined kernel (using the '-matrix' option to compute-weights), then the file specified by the '-test' option should contain a kernel matrix, rather than test set examples. The kernel matrix is an n+1 (rows) by m+1 (columns) RDB matrix, where n is the number of test examples and m is the number of training examples. The first row and column contain data labels. The matrix entry for row x, column y, contains the kernel value K(x,y). If a kernel matrix is supplied in place of the test set, then no training set need be specified. However, if the kernel is normalized or is radial basis, then the '-selftrain' and '-selftest' files must be supplied (see below).

Output: A three-column RDB file containing data labels, classifications (-1 or 1) and discriminants for the test set.

Options:

Calls: cat, column, headchg, awk


SVM