linclassif - predict labels by a linear classification rule

       linclassif  was   written   by   Vojtech   Franc   <xfrancv@cmp.felk.cvut.cz>   and   Soeren   Sonnenburg
       <Soeren.Sonnenburg@tu-berlin.de>.

       This  manual  page  was  written by Christian Kastner <debian@kvr.at>, for the Debian project (and may be
       used by others).

                                                 August 24, 2014                                   LINCLASSIF(1)

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.

       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 - predict labels by a linear classification rule

       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.

       -oout_file
              Save predictions to the file out_file.

       -t(0|1)
              Output type:

                   0 ... predicted labels (default)

                   1 ... discriminant values

svmocas(1), msvmocas(1).

linclassif [options] example_filemodel_file