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linclassif - 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 -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

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