mlearning: Machine Learning Algorithms with Unified Interface and Confusion Matrices

A unified interface is provided to various machine learning algorithms like linear or quadratic discriminant analysis, k-nearest neighbors, random forest, support vector machine, ... It allows to train, test, and apply cross-validation using similar functions and function arguments with a minimalist and clean, formula-based interface. Missing data are processed the same way as base and stats R functions for all algorithms, both in training and testing. Confusion matrices are also provided with a rich set of metrics calculated and a few specific plots.

Version:	1.2.1
Depends:	R (≥ 3.0.4)
Imports:	stats, grDevices, class, nnet, MASS, e1071, randomForest, ipred, rpart
Suggests:	mlbench, datasets, RColorBrewer, spelling, knitr, rmarkdown, covr
Published:	2023-08-30
DOI:	10.32614/CRAN.package.mlearning
Author:	Philippe Grosjean [aut, cre], Kevin Denis [aut]
Maintainer:	Philippe Grosjean <phgrosjean at sciviews.org>
BugReports:	https://github.com/SciViews/mlearning/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://www.sciviews.org/mlearning/
NeedsCompilation:	no
Language:	en-US
Materials:	NEWS
CRAN checks:	mlearning results

Documentation:

Reference manual:

mlearning.pdf

Downloads:

Package source:	mlearning_1.2.1.tar.gz
Windows binaries:	r-devel: mlearning_1.2.1.zip, r-release: mlearning_1.2.1.zip, r-oldrel: mlearning_1.2.1.zip
macOS binaries:	r-release (arm64): mlearning_1.2.1.tgz, r-oldrel (arm64): mlearning_1.2.1.tgz, r-release (x86_64): mlearning_1.2.1.tgz, r-oldrel (x86_64): mlearning_1.2.1.tgz
Old sources:	mlearning archive

Reverse dependencies:

Reverse depends:

zooimage

Linking:

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