Provided by: herisvm_0.7.0-1_all 

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)