Classification, Regression and Feature Evaluation


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Documentation for package ‘CORElearn’ version 1.56.0

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CORElearn-package R port of CORElearn
allTests Verification of the CORElearn installation
applyCalibration Calibration of probabilities according to the given prior.
applyDiscretization Discretization of numeric attributes
attrEval Attribute evaluation
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 R port of CORElearn
CORElearn-internal Internal structures of CORElearn C++ part
CoreModel Build a classification or regression model
cvCoreModel Build a classification or regression model
cvGen Cross-validation and stratified cross-validation
cvGenStratified Cross-validation and stratified cross-validation
destroyModels Destroy single model or all CORElearn models
discretize Discretization of numeric attributes
display Displaying decision and regression trees
display.CoreModel Displaying decision and regression trees
gatherFromList Cross-validation and stratified cross-validation
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
help.Core Description of parameters.
helpCore Description of parameters.
infoCore Description of certain CORElearn parameters
intervalMidPoint Discretization of numeric attributes
loadRF Saves/loads random forests model to/from file
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
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
plotOrdEval Visualization of ordEval results
predict Prediction using constructed model
predict.CoreModel Prediction using constructed model
preparePlot Prepare graphics device
preparePlot.Core Prepare graphics device
printOrdEval Visualization of ordEval results
regDataGen Artificial data for testing regression algorithms
reliabilityPlot Plots reliability plot of probabilities
rfAttrEval Attribute evaluation with random forest
rfAttrEvalClustering 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
testClassPseudoRandom Test functions for manual usage
testCore Verification of the CORElearn installation
testCoreAttrEval Verification of the CORElearn installation
testCoreClass Verification of the CORElearn installation
testCoreNA Verification of the CORElearn installation
testCoreOrdEval Verification of the CORElearn installation
testCoreRand Verification of the CORElearn installation
testCoreReg Verification of the CORElearn installation
testCoreRPORT Verification of the CORElearn installation
testTime Test functions for manual usage
versionCore Package version