Last Change: 2018-09-07, 16:50
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heri−eval − evaluate classification algorithm
heri-eval [ OPTIONS ] dataset [−− SVM_TRAIN_OPTIONS ]
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.
−h, −−help
Display help information.
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−f |
Enable output of per-fold statistics. See −Mf. |
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−n N |
N−fold cross validation mode (mandatory option). |
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−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).
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−K |
Keep temporary directory after exiting. |
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−D |
Turn on the debugging mode, implies −K. |
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).
<http://github.com/cheusov/herisvm>
heri−split(1) heri−stat(1)