This is the command svmocas that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
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
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