debian/0000755000000000000000000000000011767405034007175 5ustar debian/python-libsvm.preinst0000644000000000000000000000150411766573373013431 0ustar #!/bin/sh set -e PYCENTRAL=/usr/bin/pycentral if [ "$1" = upgrade ] then if dpkg --compare-versions "$2" lt 0.17.4-2 ; then if [ -x $PYCENTRAL ]; then pycentral pkgremove python-libsvm fi fi for pyversion in 2.4 2.5 2.6; do if [ -f /usr/lib/python$pyversion/site-packages/svmc.so ]; then rm -f /usr/lib/python$pyversion/site-packages/svmc.so fi if [ -f /usr/share/pyshared/svm.py ]; then rm -f /usr/share/pyshared/svm.py fi if [ -f /usr/lib/pyshared/python$pyversion/svmc.so ]; then rm -f /usr/lib/pyshared/python$pyversion/svmc.so fi if [ -f /usr/lib/python$pyversion/site-packages/svm.py ]; then rm -f /usr/lib/python$pyversion/site-packages/svm.py fi done fi #DEBHELPER# debian/libsvm3.postinst0000644000000000000000000000165511766573373012403 0ustar #! /bin/sh # postinst script for libsvm # # see: dh_installdeb(1) set -e # summary of how this script can be called: # * `configure' # * `abort-upgrade' # * `abort-remove' `in-favour' # # * `abort-deconfigure' `in-favour' # `removing' # # for details, see http://www.debian.org/doc/debian-policy/ or # the debian-policy package # case "$1" in configure) ldconfig ;; abort-upgrade|abort-remove|abort-deconfigure) ;; *) echo "postinst called with unknown argument \`$1'" >&2 exit 1 ;; esac # dh_installdeb will replace this with shell code automatically # generated by other debhelper scripts. #DEBHELPER# exit 0 debian/doc/0000755000000000000000000000000011766670110007740 5ustar debian/doc/svm-easy.10000644000000000000000000000141411766573373011603 0ustar .TH svm-easy 1 "DEC 2009" Linux "User Manuals" .SH NAME svm-easy \- an automatic script for LIBSVM .SH SYNOPSIS .B svm-easy .I training_file .B [ .I testing_file .B ] .SH DESCRIPTION .B svm-easy is an automatic script for LIBSVM. It will execute .BR svm-scale (1) and .BR svm-train (1) with default parameters. If the .I testing_file is specified, .BR svm-predict (1) will also be used. .SH FILES See .BR svm-train (1) for the format of .I traning_file and .I testing_file .SH EXAMPLES .IP svm-easy train.2 .IP svm-easy train.3 test.3 .SH BUGS Please report bugs to the Debian BTS. .SH AUTHOR Chih-Chung Chang, Chih-Jen Lin , Chen-Tse Tsai (packaging) .SH "SEE ALSO" .BR svm-train (1), .BR svm-predict (1), .BR svm-scale (1) debian/doc/svm-scale.10000644000000000000000000000276711766670065011741 0ustar .\" Process this file with .\" groff -man -Tascii svm-scale.1 .\" .TH svm-scale 1 "MAY 2006" Linux "User Manuals" .SH NAME svm-scale \- scale data to a restricted range as preprocessing for SVM training .SH SYNOPSIS .B svm-scale [ -l .I lower .B ] [ -u .I upper .B ] [ -y .I y_upper .B ] [ -s .I save_filename .B ] [ -r .I restore_filename ] .I datafilename .SH DESCRIPTION .B svm-scale reads the given .I datafilename (a training or testing data file as specified in .BR svm_train(1) or .BR svm_predict(1) ) and scales all dimensions to the given ranges. .SH OPTIONS .IP "-l lower" .I lower is the lowest (minimal) value allowed in each dimension. It defaults to \-1. .IP "-u upper" .I upper is the highest (maximal) value allowed in each dimension. It defaults to 1. .IP "-y y_lower" .I y_lower is a boolean value (0 or 1) indicating whether or not y-values (targets) should be scaled. It defaults to 0. .IP "-s save_filename" .I save_filename indicates the filename to save the scaled data to. .IP "-r restore_filename" .I restore_filename indicates the filename reserved to hold the original (unscaled) data in case there is a need to restore. .SH FILES .I datafilename must be a training or testing dataset. .SH ENVIRONMENT No environment variables. .SH DIAGNOSTICS None documented; see Vapnik et al. .SH BUGS Please report bugs to the Debian BTS. .SH AUTHOR Chih-Chung Chang, Chih-Jen Lin , Chen-Tse Tsai (packaging) .SH "SEE ALSO" .BR svm-train (1), .BR svm-predict (1) debian/doc/svm-predict.10000644000000000000000000000621411766573373012277 0ustar .\" Process this file with .\" groff -man -Tascii svm-predict.1 .\" .TH svm-predict 1 "MAY 2006" Linux "User Manuals" .SH NAME svm-predict \- make predictions based on a trained SVM model file and test data .SH SYNOPSIS .B svm-predict [ -b .I probability_estimates ] [ -q ] .I test_data .I model_file .I [ output_file ] .SH DESCRIPTION .B svm-predict uses a Support Vector Machine specified by a given input .I model_file to make predictions for each of the samples in .I test_data The format of this file is identical to the training_data file used in .BR svm_train(1) and is just a sparse vector as follows: .TP