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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:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=mlearning
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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