NAME

       svmocas - train a binary linear SVM classifier

SYNOPSIS

       svmocas [options] example_file model_file

DESCRIPTION

       svmocas  is  a  program  that  trains  a  binary  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+w0. model_file contains d lines, where d is the number of data
       dimensions. The first n lines are coordinates of w and the last line is w0.

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)

       -C constants_file
              If specified, each example has a different regularization  constant,  taken  from  the  text  file
              constants_file.  Each  line  of the text file must contain a single constant (positive double) for
              the corresponding example. If -C is used, then the -c option is ignored.

       -b (0|1)
              Value of the L2-bias feature. A value of 0 implies not having bias.  (default: 0)

       -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)

       -p integer
              Number of threads. (default: 1)

       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 binary SVM classifier  from  riply_trn.light,  with  the  regularization  constant  C=10,  bias
       switched on, 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 with linclassif(1) 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

SEE ALSO

       msvmocas(1), linclassif(1).

AUTHORS

       svmocas   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 <ckk@debian.org> for the Debian project (and may be
       used by others).

                                                  June 16, 2010                                       SVMOCAS(1)