svm-grid(1) [debian man page]

svm-grid(1)							   User Manuals 						       svm-grid(1)

NAME

       svm-grid - a parameter selection tool for LIBSVM

SYNOPSIS

       svm-grid  [-log2c  begin,end,step  ] [ -log2g begin,end,step ] [ -v fold ] [ -svmtrain pathname ] [ -gnuplot pathname ] [ -out pathname ] [
       -png pathname ] [ additional_parameters_for_svm-train ] dataset

DESCRIPTION

       grid.py is a parameter selection tool for C-SVM classification using the RBF (radial basis function) kernel. It uses cross validation  (CV)
       technique  to  estimate	the  accuracy of each parameter combination in the specified range and helps you to decide the best parameters for
       your problem.

FILES

       See svm-train(1) for the format of dataset

EXAMPLES

       svm-grid -log2c -5,5,1 -log2g -4,0,1 -v 5 -m 300 heart_scale

BUGS

       Please report bugs to the Debian BTS.

AUTHOR

       Chih-Chung Chang, Chih-Jen Lin <cjlin@csie.ntu.edu.tw>, Chen-Tse Tsai <ctse.tsai@gmail.com> (packaging)

SEE ALSO

       svm-train(1), svm-predict(1)

Linux								     DEC 2009							       svm-grid(1)

svm-subset(1)							   User Manuals 						     svm-subset(1)

NAME

       svm-subset - a subset selection tool for LIBSVM

SYNOPSIS

       svm-subset [ -s method ] dataset number [ output1 ] [ output2 ]

DESCRIPTION

       Training  large data is time consuming. Sometimes one should work on a smaller subset first. The python script subset.py randomly selects a
       specified number of samples. For classification data, we provide a stratified selection to ensure the same class distribution in  the  sub-
       set.

OPTIONS

       -s method

       0      -- stratified selection (classification only) (default)

       1      -- random selection

       output1
	      The subset. If output1 is omitted, the subset will be printed on the screen.

       output2
	      The rest of data.

FILES

       See svm-train(1) for the format of dataset

EXAMPLES

	      svm-subset heart_scale 100 file1 file2

       From heart_scale 100 samples are randomly selected and stored in file1. All remaining instances are stored in file2.

BUGS

       Please report bugs to the Debian BTS.

AUTHOR

       Chih-Chung Chang, Chih-Jen Lin <cjlin@csie.ntu.edu.tw>, Chen-Tse Tsai <ctse.tsai@gmail.com> (packaging)

SEE ALSO

       svm-train(1), svm-predict(1)

Linux								     DEC 2009							     svm-subset(1)