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mlearning

Machine Learning Algorithms with Unified Interface and Confusion Matrices

v1.2.1 · Aug 30, 2023 · GPL (>= 2)

Description

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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

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Reverse Dependencies (1)

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Dependency Network

Dependencies Reverse dependencies class nnet MASS e1071 randomForest ipred rpart zooimage mlearning

Version History

4 tracked
new 1.2.1 Mar 10, 2026
updated 1.2.1 ← 1.1.1 diff Aug 29, 2023
updated 1.1.1 ← 1.0-0 diff Apr 25, 2022
new 1.0-0 Jan 29, 2013