NAME

       heri-eval - evaluate classification algorithm

SYNOPSIS

       heri-eval [OPTIONS] dataset [-- SVM_TRAIN_OPTIONS]

DESCRIPTION

       heri-eval runs training algorithm on dataset and then evaluate it using testing set,
       specified by option -e.  Alternatively, cross-validation is run, if option -n was applied.
       If cross-validation is used, training and testing on different folds are run in parallel,
       thus utilizing available CPUs.

OPTIONS

       -h, --help
             Display help information.

       -f    Enable output of per-fold statistics. See -Mf.

       -n N  N-fold cross validation mode (mandatory option).

       -t T  T*N-fold cross validation mode (1 by default).

       -e testing set
             Sets the testing dataset.

       -o filename
             Save results from testing sets to the specified file.

             Format: golden_class result_class [score]

       -O filename
             Save incorrectly classified objects to the specified file.

             Format: #object_number: golden_class result_class [score])

       -m filename
             Save confusion matrix to the specified file.

             Format: frequency : golden_class result_class

       -p opts
             Pass the specified opts to heri-stat(1)

       -M chars
             Sets the output mode where chars are: t -- output total statistics, f -- output per-
             fold statistics, c -- output cross-fold statistics.  The default is "-M tc".

       -S seed
             Pass the specified seed to heri-split(1).

       -K    Keep temporary directory after exiting.

       -D    Turn on the debugging mode, implies -K.

ENVIRONMENT

       SVM_TRAIN_CMD
             Training utility, e.g., liblinear-train (the default is svm-train).

       SVM_PREDICT_CMD
             Predicting utility, e.g., liblinear-predict (the default is svm-predict).

       TMPDIR
             Temporary directory (the default is /tmp).

HOME

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

SEE ALSO

       heri-split(1) heri-stat(1)

                                            2016-02-29                               heri-eval(1)