CORElearn: CORElearn - classification, regression, feature evaluation and
CORElearn is machine learning suite ported to R from
standalone C++ package. It contains several model learning
techniques in classification and regression, for example
classification and regression trees with optional constructive
induction and models in the leafs, random forests, kNN, naive
Bayes, and locally weighted regression. It is especially
strong in feature evaluation algorithms where it contains
several variants of Relief algorithm and many impurity based
attribute evaluation functions, e.g., Gini, information gain,
MDL, DKM, ... Its additional strength is ordEval algorithm and
its visualization used for ordinal features and class. Several
algorithms support parallel multithreaded execution via OpenMP.
Windows binary versions supporting multithreading are available
on package website, as CRAN uses different toolchain. The top
level documentation is reachable through ?CORElearn.