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


heri-stat - calculates precision, recall, F1 and some other things


heri-stat [-R] [-mrca] [-u label] [-t threshold]
outcomes_file predictions_file

heri-stat -1 [-R] [-mrca] [-u label] [-t threshold]

heri-stat -g mode [-R] [-xy] outcomes_file predictions_file

heri-stat -1 -g mode [-R] [files...]

heri-stat [-h]


The first and second types of heri-stat invocation takes classification dataset and predictions on input, and calculate precision, recall and F1. Unless option -1 was applied, heri-stat reads correct classes from outcomes_file (one class per line) and predicted classes from predictions_file (one class per line). It is allowed for predictions_file to contain two tokens per line. The first one is a predicted class, the second one is a score, e.g. probability.

The third and forth type of heri-stat invocation takes regression outcomes and predictions on input (one value per line) and calculate mean absolute error (MAE), mean squared error (MSE) and/or mean absolute error (MAE).

If -1 was applied, two or three tokens per line are expected on input: correct value (or class for classification), predicted value (or class), and optional score.


Display help information.
Raw tab-separated output.
Disable micro averaged P/R/F1 output.
Disable macro averaged P/R/F1 output.
Disable output of per-class statistics.
Disable output of accuracy.
-1, --single
2 or 3 tokens per line are expected on input.
Set the label for "unclassified" object. If specified, micro-averaged P/R/F1 is calculated instead of accuracy. Also, statistics for this class is not calculated.
Consider classes with score less than the specified value as unclassified.
Regression outcomes and predictions are expected on input. If mode contains symbol a, MAE is output, s -- MSE, and r -- RMSE is output.




heri-eval(1) heri-split(1)