Description
For classification/ranking: ROC AUC, BEDROC AUC, Enrichment Factor, Robust Initial Enhancement, Power Metric, Matthews' Correlation Coefficient, Platt scaling.
For regression: Root Mean Squared Error, Mean Absolute Error, r^2 coefficient of determination, Raw Regression Error Characteristic Curve.
Also features a TopKeeper module; to keep in memory the top 'k' scored items when dealing with very large datasets.
Published: 21 Dec 2022
The Classification and Regression Performance Metrics library
Install
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Authors
Maintainers
Sources
v12.2.0.tar.gz
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