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: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=mlearning to link to this page.
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