CORElearn swMATH ID: 10624 Software Authors: Marko Robnik-Sikonja, Petr Savicky Description: R package CORElearn: Classification, regression, feature evaluation and ordinal evaluation. 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 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 evaluation of data sets with ordinal features and class. Several algorithms support parallel multithreaded execution via OpenMP. The top level documentation is reachable through ?CORElearn. Homepage: http://cran.r-project.org/web/packages/CORElearn/index.html Source Code: https://github.com/cran/CORElearn Dependencies: R Related Software: R; caret; mlr; RWeka; CRAN; nnet; e1071; C50; Kernlab; randomForest; ipred; mogavs; GenAlgo; gaselect; EFS; featurefinder; varSelRF; GeneSrF; spFSR; Boruta Cited in: 4 Publications all top 5 Cited by 15 Authors 1 Bagnato, Luca 1 Bischl, Bernd 1 Casalicchio, Giuseppe 1 Johnson, Kjell 1 Jones, Zachary M. 1 Kotthoff, Lars 1 Kuhn, Max 1 Lang, Michel 1 Punzo, Antonio 1 Richter, Jakob 1 Schiffner, Julia 1 Schmid, Matthias 1 Studerus, Erich 1 Tomarchio, Salvatore D. 1 Welchowski, Thomas Cited in 3 Serials 1 Computational Statistics 1 Journal of Machine Learning Research (JMLR) 1 AStA. Advances in Statistical Analysis Cited in 3 Fields 4 Statistics (62-XX) 2 Computer science (68-XX) 1 General and overarching topics; collections (00-XX) Citations by Year