| 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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