Provided by: libocas-tools_0.97+dfsg-6_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)