CORElearn: Classification, Regression and Feature Evaluation
Version 1.50.3

A suite of machine learning algorithms written in C++ with R interface contains several learning techniques for classification and regression, Predictive models include e.g., classification and regression trees with optional constructive induction and models in the leaves, random forests, kNN, naive Bayes, and locally weighted regression. All predictions obtained with these models can be explained and visualized with ExplainPrediction package. The package 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, and DKM. These methods can be used for feature selection or discretization of numeric attributes. The OrdEval algorithm and its visualization is used for evaluation of data sets with ordinal features and class, enabling analysis according to the Kano model of customer satisfaction. Several algorithms support parallel multithreaded execution via OpenMP. The top-level documentation is reachable through ?CORElearn.

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AuthorMarko Robnik-Sikonja and Petr Savicky
Date of publication2017-03-28 15:27:04 UTC
Maintainer"Marko Robnik-Sikonja" <marko.robnik@fri.uni-lj.si>
LicenseGPL-3
Version1.50.3
URL http://lkm.fri.uni-lj.si/rmarko/software/
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("CORElearn")

Man pages

attrEval: Attribute evaluation
auxTest: Test functions for manual usage
calibrate: Calibration of probabilities according to the given prior.
classDataGen: Artificial data for testing classification algorithms
classPrototypes: The typical instances of each class - class prototypes
CORElearn-internal: Internal structures of CORElearn C++ part
CORElearn-package: R port of CORElearn
CoreModel: Build a classification or regression model
destroyModels: Destroy single model or all CORElearn models
discretize: Discretization of numeric attributes
display.CoreModel: Displaying decision and regression trees
getCoreModel: Conversion of model to a list
getRFsizes: Get sizes of the trees in RF
getRpartModel: Conversion of a CoreModel tree into a rpart.object
helpCore: Description of parameters.
infoCore: Description of certain CORElearn parameters
modelEval: Statistical evaluation of predictions
noEqualRows: Number of equal rows in two data sets
ordDataGen: Artificial data for testing ordEval algorithms
ordEval: Evaluation of ordered attributes
paramCoreIO: Input/output of parameters from/to file
plot.CoreModel: Visualization of CoreModel models
plot.ordEval: Visualization of ordEval results
predict.CoreModel: Prediction using constructed model
preparePlot: Prepare graphics device
regDataGen: Artificial data for testing regression algorithms
reliabiltyPlot: Plots reliability plot of probabilities
rfAttrEval: Attribute evaluation with random forest
rfClustering: Random forest based clustering
rfOOB: Out-of-bag performance estimation for random forests
rfOutliers: Random forest based outlier detection
rfProximity: A random forest based proximity function
saveRF: Saves/loads random forests model to/from file
testCore: Verification of the CORElearn installation
versionCore: Package version

Functions

CORElearn Man page
CORElearn-internal Man page
CORElearn-package Man page
CoreModel Man page Source code
allTests Man page Source code
applyCalibration Man page Source code
applyDiscretization Man page Source code
asTxt Source code
attrEval Man page Source code
attrNormBarObject Source code
avNormBarObject Source code
avSlopeObject Source code
basicStrong Source code
basicWeak Source code
boxwhiskers Source code
calibrate Man page Source code
checkDataOptions Source code
checkEstimatorOptions Source code
checkModelOptions Source code
checkOptionsValues Source code
checkOrdEvalOptions Source code
checkPredictOptions Source code
classDataGen Man page Source code
classPrototypes Man page Source code
cmp.table Source code
compareApprox Source code
compareClass Source code
compareMEval Source code
comparePredict Source code
convert.Options Source code
destroyCore Source code
destroyModels Man page Source code
discretize Man page Source code
display Man page Source code
display.CoreModel Man page Source code
distGen Source code
excitementStrong Source code
excitementWeak Source code
forceDist Source code
get.formula Source code
getCoreModel Man page Source code
getQuartils Source code
getRFsizes Man page Source code
getRpart Source code
getRpartModel Man page Source code
getStatNames Source code
getVarImportanceCluster Source code
help.Core Man page
helpCore Man page
infoCore Man page Source code
initCore Source code
intervalMidPoint Man page Source code
intervalNames Source code
loadRF Man page Source code
modelEval Man page Source code
modelEvaluationClass.Core Source code
modelEvaluationReg.Core Source code
noEqualRows Man page Source code
oeInst Source code
onLoad Source code
onUnload Source code
optDefault Source code
optionData Source code
ordDataGen Man page Source code
ordEval Man page Source code
outputResult Source code
paramCoreIO Man page Source code
performanceStrong Source code
performanceWeak Source code
plot.CoreModel Man page Source code
plot.ordEval Man page Source code
plotInstEval Source code
plotOrdEval Man page Source code
plotRFMulti Source code
plotRFNorm Source code
plotRFStats Source code
predict Man page Source code
predict.CoreModel Man page Source code
prepare.Data Source code
prepare.Options Source code
preparePlot Man page Source code
preparePlot.Core Man page
printOrdEval Man page Source code
regDataGen Man page Source code
reliabilityPlot Man page Source code
rfAttrEval Man page Source code
rfAttrEvalClustering Man page Source code
rfClustering Man page Source code
rfOOB Man page Source code
rfOutliers Man page Source code
rfProximity Man page Source code
rpart.formatg Source code
saveRF Man page Source code
singleTestNA Source code
spaceScale Source code
testClassPseudoRandom Man page Source code
testCore Man page
testCoreAttrEval Man page Source code
testCoreClass Man page Source code
testCoreNA Man page Source code
testCoreOrdEval Man page Source code
testCoreRPORT Man page Source code
testCoreRand Man page Source code
testCoreReg Man page Source code
testTime Man page Source code
trimSpaces Source code
varNormalization Source code
versionCore Man page Source code

Files

src
src/binpart.h
src/cost.cpp
src/mstring.cpp
src/rfUtil.cpp
src/estimator.h
src/exprReg.cpp
src/binnodeReg.h
src/Rfront.h
src/ftree.cpp
src/binarizeReg.cpp
src/random.cpp
src/rrelieff.cpp
src/rfUtil.h
src/bintree.cpp
src/rfVisualFront.cpp
src/dataStore.cpp
src/frontend.h
src/options.h
src/binnodeReg.cpp
src/nrutil.h
src/error.h
src/printUtil.cpp
src/relieff.cpp
src/estCommon.cpp
src/general.h
src/mathutil.h
src/binpart.cpp
src/options.cpp
src/binnode.h
src/random.h
src/trutilReg.cpp
src/mlist.h
src/new_new.h
src/constrct.h
src/kdtree.h
src/kdtree.cpp
src/frontend.cpp
src/bintreeReg.cpp
src/binnode.cpp
src/Rconvert.cpp
src/estimatorReg.cpp
src/rndforest.cpp
src/utils.h
src/bintreeReg.h
src/exprReg.h
src/utils.cpp
src/error.cpp
src/treenode.cpp
src/expr.h
src/ftree.h
src/pruneReg.cpp
src/Makevars.in
src/expr.cpp
src/new_new.cpp
src/bintree.h
src/calibrate.cpp
src/mathutil.cpp
src/regtree.cpp
src/printUtil.h
src/treenodeReg.cpp
src/modelReg.cpp
src/platform_unix.h
src/model.cpp
src/estimatorReg.h
src/constrctReg.cpp
src/menu.h
src/contain.h
src/rfVisual.cpp
src/rndforest.h
src/constrctReg.h
src/estOrdAttr.cpp
src/prune.cpp
src/c45read.cpp
src/Makevars.win
src/dataStore.h
src/mstring.h
src/c45read.h
src/binarize.cpp
src/calibrate.h
src/estimator.cpp
src/nrutil.cpp
src/trutil.cpp
src/regtree.h
src/platform_win.h
src/rfRegularize.cpp
src/menu.cpp
src/constrct.cpp
src/Rfront.cpp
NAMESPACE
R
R/ordEval.R
R/init.R
R/dataGenerator.R
R/util.R
R/testCore.R
R/rfVisualize.R
R/Rinterface.R
MD5
DESCRIPTION
configure
ChangeLog
man
man/regDataGen.Rd
man/CORElearn-internal.Rd
man/CoreModel.Rd
man/plot.CoreModel.Rd
man/rfProximity.Rd
man/getCoreModel.Rd
man/getRpartModel.Rd
man/infoCore.Rd
man/testCore.Rd
man/paramCoreIO.Rd
man/destroyModels.Rd
man/helpCore.Rd
man/discretize.Rd
man/noEqualRows.Rd
man/rfClustering.Rd
man/ordDataGen.Rd
man/display.CoreModel.Rd
man/modelEval.Rd
man/classDataGen.Rd
man/saveRF.Rd
man/ordEval.Rd
man/predict.CoreModel.Rd
man/auxTest.Rd
man/CORElearn-package.Rd
man/versionCore.Rd
man/rfOutliers.Rd
man/getRFsizes.Rd
man/attrEval.Rd
man/rfAttrEval.Rd
man/reliabiltyPlot.Rd
man/classPrototypes.Rd
man/plot.ordEval.Rd
man/rfOOB.Rd
man/calibrate.Rd
man/preparePlot.Rd
configure.win
cleanup
cleanup.win
CORElearn documentation built on May 19, 2017, 5:58 p.m.