mlearning: Machine Learning Algorithms with Unified Interface and Confusion
Matrices
A unified interface is provided to various machine learning
algorithms like LDA, QDA, k-nearest neighbour, LVQ, random forest, SVM, ... 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 threated 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: |
1.1.1 |
| Depends: |
R (≥ 3.0.4) |
| Imports: |
stats, grDevices, class, nnet, MASS, e1071, randomForest, ipred |
| Suggests: |
mlbench, datasets, RColorBrewer |
| Published: |
2022-04-26 |
| Author: |
Philippe Grosjean [aut, cre],
Kevin Denis [aut] |
| Maintainer: |
Philippe Grosjean <phgrosjean at sciviews.org> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://www.sciviews.org/mlearning/ |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
mlearning results |
Documentation:
Downloads:
Reverse dependencies:
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