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 |