svmocas - Online in the Cloud

PROGRAM:

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

Use svmocas online using onworks.net services