Machine Learning Model Evaluation

Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. 'MLeval' produces a range of evaluation metrics with confidence intervals.


Reference manual

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0.3 by Christopher R John, a year ago

Browse source code at

Authors: Christopher R John

Documentation:   PDF Manual  

AGPL-3 license

Imports ggplot2

Suggests knitr, rmarkdown

See at CRAN