Predict labels by a linear classification rule
linclassif [options] example_file model_file
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.
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
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
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).