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CORElearn (version 0.9.29)

CORElearn - classification, regression, feature evaluation and ordinal evaluation

Description

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. The top level documentation is reachable through ?CORElearn.

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Version

Install

install.packages('CORElearn')

Monthly Downloads

3,065

Version

0.9.29

License

GPL (>= 3)

Maintainer

Marko Robnik-Sikonja

Last Published

September 8th, 2010

Functions in CORElearn (0.9.29)

plot.ordEval

Visualization of ordEval results
classDataGen

Artificial data for testing classification algorithms
calibrate

Calibration of probabilities according to the given prior.
versionCore

Package version
CORElearn-internal

Internal structures of CORElearn C++ part
infoCore

Description of certain CORElearn parameters
getCoreModel

Conversion of model to a list
ordEval

Evaluation of ordered attributes
getRFsizes

Get sizes of the trees in RF
regDataGen

Artificial data for testing regression algorithms
helpCore

Description of parameters.
destroyModels

Destroy single or all CORElearn models
ordDataGen

Artificial data for testing ordEval algorithms
modelEval

Statistical evaluation of predictions
CORElearn-package

R port of CORElearn
preparePlot

Prepare graphics device
CoreModel

Build a classification or regression model
paramCoreIO

Input/output of parameters from/to file
testCore

Verification of the CORElearn installation
attrEval

Attribute evaluation
saveRF

Saves/loads random forests model to/from file
auxTest

Test functions for manual usage
rfAttrEval

Attribute evaluation with random forest
predict.CoreModel

Prediction using constructed model