linclassif(1) predict labels by a linear classification rule

SYNOPSIS

linclassif [options] example_file model_file

DESCRIPTION

linclassif is a program that predicts labels by a linear classification rule.

example_file is a file with testing examples in SVM^light format, and model_file is the file which contains either a binary (two-class) rule f(x)=w'*x+w0 or a multi-class rule f(x)=W'*x. These are produced svmocas(1) and msvmocas(1), respectively.

OPTIONS

A summary of options is included below.
-h
Show summary of options.
-v (0|1)
Set the verbosity level (default: 1)
-e
Print the classification error computed from predicted labels and labels contained in example_file.
-o out_file
Save predictions to the file out_file.
-t (0|1)
Output type:

0 ... predicted labels (default)

1 ... discriminant values

EXAMPLES

Train the multi-class SVM classifier from example file fiply_trn.light, using svmocas(1) with the regularization constant C=10, verbosity switched off, and save model to svmocas.model:

 svmocas -c 10 -b 1 -v 0 riply_trn.light svmocas.model

Compute the testing error of the classifier stored in svmocas.model using testing examples from riply_tst.light and save the predicted labels to riply_tst.pred:

 linclassif -e -o riply_tst.pred riply_tst.light svmocas.model

AUTHORS

linclassif was written by Vojtech Franc <[email protected]> and Soeren Sonnenburg <[email protected]>.

This manual page was written by Christian Kastner <[email protected]>, for the Debian project (and may be used by others).