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 |
cvGen | Cross-validation and stratified cross-validation |
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 |
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