Provided by: libocas-tools_0.97+dfsg-5_amd64 bug

NAME

       msvmocas - train a multi-class linear SVM classifier

SYNOPSIS

       msvmocas [options] example_file model_file

DESCRIPTION

       msvmocas  is a program that trains a multi-class linear SVM classifier using the Optimized
       Cutting Plane Algorithm for Support Vector Machines (OCAS) and produces a model file.

       example_file is a file with training examples in SVM^light format, and model_file  is  the
       file  in  which  to store the learned linear rule f(x)=W'*x. model_file contains M columns
       and D lines,  where  M  is  the  number  of  classes  and  D  the  number  of  dimensions,
       corresponding to the elements of the matrix W [D x M].

OPTIONS

       A summary of options is included below.

       General options:

       -h     Show summary of options.

       -v (0|1)
              Set the verbosity level (default: 1)

       Learning options:

       -c float
              Regularization constant C. (default: 1)

       -n integer
              Use  only  the  first integer examples for training. By default, integer equals the
              number of examples in example_file.

       Optimization options:

       -m (0|1)
              Solver to be used:

                   0 ... standard cutting plane (equivalent to BMRM, SVM^perf)

                   1 ... OCAS (default)

       -s integer
              Cache size for cutting planes. (default: 2000)

       Stopping conditions:

       -a float
              Absolute tolerance TolAbs: halt if QP-QD <= TolAbs. (default: 0)

       -r float
              Relative tolerance TolAbs: halt if QP-QD <= abs(QP)*TolRel.  (default: 0.01)

       -q float
              Desired objective value QPValue: halt is QP <= QPValue. (default: 0)

       -t float
              Halts if the solver time (loading time is not counted) exceeds the  time  given  in
              seconds. (default: infinity)

EXAMPLES

       Train  the  multi-class  SVM  classifier  from example file example4_train.light, with the
       regularization constant C=10, verbosity switched off, and save model to msvmocas.model:

                    msvmocas -c 10 -v 0 example4_train.light msvmocas.model

       Compute the testing error of the classifier stored in  msvmocas.model  with  linclassif(1)
       using  testing  examples  from  example4_test.light  and  save  the  predicted  labels  to
       example4_test.pred:

                    linclassif -e -o example4_test.pred example4_test.light msvmocas.model

SEE ALSO

       svmocas(1), linclassif(1).

AUTHORS

       msvmocas 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).

                                          June 16, 2010                               MSVMOCAS(1)