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 |
| 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 |
| Reference manual: | mlearning.html , mlearning.pdf |
| 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 depends: | zooimage |
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