MLeval: 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.

Version: 0.3
Depends: R (≥ 3.5.0)
Imports: ggplot2
Suggests: knitr, rmarkdown
Published: 2020-02-12
Author: Christopher R John
Maintainer: Christopher R John <chris.r.john86 at>
License: AGPL-3
NeedsCompilation: no
CRAN checks: MLeval results


Reference manual: MLeval.pdf
Vignettes: MLeval


Package source: MLeval_0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): MLeval_0.3.tgz, r-oldrel (arm64): MLeval_0.3.tgz, r-release (x86_64): MLeval_0.3.tgz, r-oldrel (x86_64): MLeval_0.3.tgz
Old sources: MLeval archive


Please use the canonical form to link to this page.