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
DOI:	10.32614/CRAN.package.MLeval
Author:	Christopher R John
Maintainer:	Christopher R John <chris.r.john86 at gmail.com>
License:	AGPL-3
NeedsCompilation:	no
CRAN checks:	MLeval results

Documentation:

Reference manual:	MLeval.pdf
Vignettes:	MLeval (source, R code)

Downloads:

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

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