.\" Hey, EMACS: -*- nroff -*- .TH SVMOCAS 1 "June 16, 2010" .SH NAME svmocas \- train a binary linear SVM classifier .SH SYNOPSIS .B svmocas .RI [ options ] " example_file " \fImodel_file\fP .SH DESCRIPTION \fBsvmocas\fP 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. .PP \fIexample_file\fP is a file with training examples in SVM^light format, and \fImodel_file\fP is the file in which to store the learned linear rule \fBf(x)=w'*x+w0\fP. \fImodel_file\fP contains \fBd\fP lines, where \fBd\fP is the number of data dimensions. The first n lines are coordinates of \fBw\fP and the last line is \fBw0\fP. .SH OPTIONS A summary of options is included below. .PP \fBGeneral options:\fP .TP .B \-h Show summary of options. .TP .B \-v \fI(0|1)\fP Set the verbosity level (default: \fB1\fP) .PP \fBLearning options:\fP .TP .B \-c \fIfloat\fB Regularization constant C. (default: \fB1\fP) .TP .B \-C \fIconstants_file\fB If specified, each example has a different regularization constant, taken from the text file \fIconstants_file\fP. Each line of the text file must contain a single constant (positive double) for the corresponding example. If \fB-C\fP is used, then the \fB-c\fP option is ignored. .TP .B \-b \fI(0|1)\fP Value of the L2-bias feature. A value of 0 implies not having bias. (default: \fB0\fP) .TP .B \-n \fIinteger\fP Use only the first \fIinteger\fP examples for training. By default, \fIinteger\fP equals the number of examples in \fIexample_file\fP. .PP \fBOptimization options:\fP .TP .B \-m \fI(0|1)\fP Solver to be used: .sp .RS 12 .nf 0 ... standard cutting plane (equivalent to BMRM, SVM^perf) .sp 1 ... OCAS (default) .fi .RE .TP .B \-s \fIinteger\fP Cache size for cutting planes. (default: \fB2000\fP) .TP .B \-p \fIinteger\fP Number of threads. (default: \fB1\fP) .PP \fBStopping conditions:\fP .TP .B \-a \fIfloat\fP Absolute tolerance TolAbs: halt if \fBQP-QD <= TolAbs\fP. (default: \fB0\fP) .TP .B \-r \fIfloat\fP Relative tolerance TolAbs: halt if \fBQP-QD <= abs(QP)*TolRel\fP. (default: \fB0.01\fP) .TP .B \-q \fIfloat\fP Desired objective value QPValue: halt is \fBQP <= QPValue\fP. (default: \fB0\fP) .TP .B \-t \fIfloat\fP Halts if the solver time (loading time is not counted) exceeds the time given in seconds. (default: \fBinfinity\fP) .SH EXAMPLES Train the binary SVM classifier from \fIriply_trn.light\fP, with the regularization constant C=10, bias switched on, verbosity switched off, and save model to \fIsvmocas.model\fP: .sp .RS 12 .nf svmocas \-c 10 \-b 1 \-v 0 riply_trn.light svmocas.model .fi .RE .sp Compute the testing error of the classifier stored in \fIsvmocas.model\fP with \fBlinclassif\fP(1) using testing examples from \fIriply_tst.light\fP and save the predicted labels to \fIriply_tst.pred\fP: .sp .RS 12 .nf linclassif \-e \-o riply_tst.pred riply_tst.light svmocas.model .fi .RE .SH SEE ALSO .BR msvmocas (1), .BR linclassif (1). .SH AUTHORS svmocas was written by Vojtech Franc and Soeren Sonnenburg . .PP This manual page was written by Christian Kastner for the Debian project (and may be used by others).