# Classification, Regression and Feature Evaluation

## Documentation for package ‘CORElearn’ version 1.53.1

- DESCRIPTION file.

## Help Pages

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
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