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 |