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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.1 |
rolling linux/jammy R-4.5 | mlearning_1.2.1.tar.gz |
225.6 KiB |
1.2.1 |
rolling linux/noble R-4.5 | mlearning_1.2.1.tar.gz |
226.0 KiB |
1.2.1 |
rolling source/ R- | mlearning_1.2.1.tar.gz |
51.2 KiB |
1.2.1 |
latest linux/jammy R-4.5 | mlearning_1.2.1.tar.gz |
225.6 KiB |
1.2.1 |
latest linux/noble R-4.5 | mlearning_1.2.1.tar.gz |
226.0 KiB |
1.2.1 |
latest source/ R- | mlearning_1.2.1.tar.gz |
51.2 KiB |
1.2.1 |
2026-04-26 source/ R- | mlearning_1.2.1.tar.gz |
51.2 KiB |
1.2.1 |
2026-04-23 source/ R- | mlearning_1.2.1.tar.gz |
51.2 KiB |
1.2.1 |
2026-04-09 windows/windows R-4.5 | mlearning_1.2.1.zip |
228.5 KiB |
1.2.1 |
2025-04-20 source/ R- | mlearning_1.2.1.tar.gz |
51.2 KiB |