NAME

       heri-split - splits the dataset into training and testing sets

SYNOPSIS

       heri-split [OPTIONS] dataset1 [dataset2...]

DESCRIPTION

       heri-split splits the dataset into several training and testing sets as it is required for
       N-fold cross-validation. Dataset contains one object per line as in svmlight format. By
       default stratified sampling is used. That is, all folds contain the same number of objects
       for each label.  If option -c is specified, testN.txt and trainN.txt files (also in
       svmlight format) are created, where N is the number of fold.  If option -R is specified,
       test.txt and train.txt files are created for the same purposes.  Also testing_fold.txt
       file is created, where for each object (one per line) its testing fold number is specified
       if oprion -c is applied.  The file testing_fold.txt contain either 1 for testing set and 0
       for training set, if option -R is applied.

OPTIONS

       -h, --help
             Display help information.

       -c, --folds count
             Set the number of folds. This is a mandatory option.

       -d, --output-dir dir
             Set the output directory. This is a mandatory option.

       -r,--random
             Use random sampling instead of stratified one.

       -R,--ratio
             Split the input dataset into training and testing one in the specified ratio (in
             percents).

       -s, --seed seed
             Set the seed value for pseudorandom generator.

HOME

       <http://github.com/cheusov/herisvm>

SEE ALSO

       heri-eval(1) heri-stat(1)

                                            2021-01-25                              heri-split(1)