A B C D E F G H I K L M N O P R S T U V W X
| randomUniformForest-package | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| A2Rplot | All internal functions |
| A2Rplot.default | All internal functions |
| A2Rplot.hclust | All internal functions |
| as.supervised | Conversion of an unsupervised model into a supervised one |
| as.true.matrix | All internal functions |
| asymetricCrossEntropyCPP | All internal functions |
| asymetricGiniCPP | All internal functions |
| asymetricInformationGainCPP | All internal functions |
| autoMPG | Auto MPG Data Set |
| bCI | Bootstrapped Prediction Intervals for Ensemble Models |
| bCICore | All internal functions |
| biasVarCov | Bias-Variance-Covariance Decomposition |
| breastCancer | Breast Cancer Wisconsin (Original) Data Set |
| carEvaluation | Car Evaluation Data Set |
| category2Proba | All internal functions |
| category2Quantile | All internal functions |
| categoryCombination | All internal functions |
| CheckSameValuesInAllAttributes | All internal functions |
| CheckSameValuesInLabels | All internal functions |
| checkUniqueObsCPP | All internal functions |
| classifyCPP | All internal functions |
| classifyMatrixCPP | All internal functions |
| clusterAnalysis | Cluster (or classes) analysis of importance objects. |
| clusteringObservations | Cluster observations of a (supervised) randomUniformForest object |
| combineRUFObjects | All internal functions |
| combineUnsupervised | Combine Unsupervised Learning objects |
| concat | All internal functions |
| concatCore | All internal functions |
| ConcreteCompressiveStrength | Concrete Compressive Strength Data Set |
| conditionalCrossEntropyCPP | All internal functions |
| conditionalGiniCPP | All internal functions |
| confusion.matrix | All internal functions |
| copulaLike | All internal functions |
| count.factor | All internal functions |
| crossEntropyCPP | All internal functions |
| cutree.order | All internal functions |
| dates2numeric | All internal functions |
| define_train_test_sets | All internal functions |
| difflog | All internal functions |
| dummy.recode | All internal functions |
| entropyInformationGainCPP | All internal functions |
| estimatePredictionAccuracy | All internal functions |
| estimaterequiredSampleSize | All internal functions |
| expectedSquaredBias | All internal functions |
| extractYFromData | All internal functions |
| factor2matrix | All internal functions |
| factor2vector | All internal functions |
| fillNA2.randomUniformForest | Missing values imputation by randomUniformForest |
| fillVariablesNames | All internal functions |
| fillWith | All internal functions |
| filter.forest | All internal functions |
| filter.object | All internal functions |
| filterOutliers | All internal functions |
| find.first.idx | All internal functions |
| find.idx | All internal functions |
| find.root | All internal functions |
| fScore | All internal functions |
| fullNDCG | All internal functions |
| fullNode | All internal functions |
| gap.stats | All internal functions |
| generalization.error | All internal functions |
| generic.cv | Generic k-fold cross-validation |
| generic.log | All internal functions |
| generic.smoothing.log | All internal functions |
| genericCbind | All internal functions |
| genericNode | All internal functions |
| genericOutput | All internal functions |
| getCorr | All internal functions |
| getOddEven | All internal functions |
| getTree | Extract a tree from a forest |
| getTree.randomUniformForest | Extract a tree from a forest |
| getVotesProbability | All internal functions |
| getVotesProbability2 | All internal functions |
| giniCPP | All internal functions |
| gMean | All internal functions |
| hClust | All internal functions |
| HuberDist | All internal functions |
| Id | All internal functions |
| importance | Variable Importance for random Uniform Forests |
| importance.randomUniformForest | Variable Importance for random Uniform Forests |
| imputeCategoryForTestData | All internal functions |
| inDummies | All internal functions |
| init_values | Training and validation samples from data |
| insert.in.vector | All internal functions |
| insert.in.vector2 | All internal functions |
| interClassesVariance | All internal functions |
| intraClassesVariance | All internal functions |
| is.wholenumber | All internal functions |
| kappaStat | All internal functions |
| kBiggestProximities | All internal functions |
| keep.index | All internal functions |
| kMeans | All internal functions |
| L1AsymetricInformationGainCPP | All internal functions |
| L1Dist | All internal functions |
| L1DistCPP | All internal functions |
| L1InformationGainCPP | All internal functions |
| L2.logDist | All internal functions |
| L2AsymetricInformationGainCPP | All internal functions |
| L2Dist | All internal functions |
| L2DistCPP | All internal functions |
| L2InformationGainCPP | All internal functions |
| lagFunction | All internal functions |
| leafNode | All internal functions |
| LInfCPP | All internal functions |
| localTreeImportance | All internal functions |
| localVariableImportance | All internal functions |
| majorityClass | All internal functions |
| matrix2factor | All internal functions |
| matrix2factor2 | All internal functions |
| MDSscale | All internal functions |
| mergeClusters | Merge two arbitrary, but adjacent, clusters |
| mergeLists | All internal functions |
| mergeOutliers | All internal functions |
| min_or_max | All internal functions |
| model.stats | Common statistics for a vector (or factor) of predictions and a vector (or factor) of responses |
| modelingResiduals | All internal functions |
| modifyClusters | Change number of clusters (and clusters shape) on the fly |
| modX | All internal functions |
| monitorOOBError | All internal functions |
| myAUC | All internal functions |
| na.impute | All internal functions |
| na.missing | All internal functions |
| na.replace | All internal functions |
| NAfactor2matrix | All internal functions |
| NAFeatures | All internal functions |
| NATreatment | All internal functions |
| ndcg | All internal functions |
| observationsImportance | All internal functions |
| onlineClassify | All internal functions |
| onlineCombineRUF | All internal functions |
| OOBquantiles | All internal functions |
| OOBVotesScale | All internal functions |
| optimizeFalsePositives | All internal functions |
| options.filter | All internal functions |
| outputPerturbationSampling | All internal functions |
| outsideConfIntLevels | All internal functions |
| overSampling | All internal functions |
| parallelNA.replace | All internal functions |
| partialDependenceBetweenPredictors | Partial Dependence between Predictors and effect over Response |
| partialDependenceOverResponses | Partial Dependence Plots and Models |
| partialImportance | Partial Importance for random Uniform Forests |
| permuteCatValues | All internal functions |
| perspWithcol | All internal functions |
| plot.importance | Variable Importance for random Uniform Forests |
| plot.randomUniformForest | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| plot.unsupervised | Unsupervised Learning with Random Uniform Forests |
| plotTree | Plot a Random Uniform Decision Tree |
| plotTreeCore | All internal functions |
| plotTreeCore2 | All internal functions |
| postProcessingVotes | Post-processing for Regression |
| predict | Predict method for random Uniform Forests objects |
| predict.randomUniformForest | Predict method for random Uniform Forests objects |
| predictDecisionTree | All internal functions |
| predictionvsResponses | All internal functions |
| print.importance | Variable Importance for random Uniform Forests |
| print.randomUniformForest | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| print.unsupervised | Unsupervised Learning with Random Uniform Forests |
| proximitiesMatrix | All internal functions |
| pseudoHuberDist | All internal functions |
| pseudoNAReplace | All internal functions |
| randomCombination | All internal functions |
| randomize | All internal functions |
| randomUniformForest | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| randomUniformForest.default | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| randomUniformForest.formula | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| randomUniformForestCore | All internal functions |
| randomUniformForestCore.big | All internal functions |
| randomUniformForestCore.merge | All internal functions |
| randomUniformForestCore.predict | All internal functions |
| randomWhichMax | All internal functions |
| rankingTrainData | All internal functions |
| reduce.trees | All internal functions |
| residualsRandomUniformForest | All internal functions |
| reSMOTE | REplication of a Synthetic Minority Oversampling TEchnique for highly imbalanced datasets |
| rewind.trees | All internal functions |
| rm.coordinates | All internal functions |
| rm.correlation | All internal functions |
| rm.InAList | All internal functions |
| rm.string | All internal functions |
| rm.tempdir | All internal functions |
| rm.trees | Remove trees from a random Uniform Forest |
| rmInAListByNames | All internal functions |
| rmInf | All internal functions |
| rmNA | All internal functions |
| rmNoise | All internal functions |
| roc.curve | ROC and precision-recall curves for random Uniform Forests |
| rollApplyFunction | All internal functions |
| rufImpute | Missing values imputation by randomUniformForest |
| runifMatrixCPP | All internal functions |
| rUniformForest.big | Random Uniform Forests for Classification and Regression with large data sets |
| rUniformForest.combine | Incremental learning for random Uniform Forests |
| rUniformForest.grow | Add trees to a random Uniform Forest |
| rUniformForest.merge | All internal functions |
| rUniformForestPredict | All internal functions |
| sampleDirichlet | All internal functions |
| scale2AnyValues | All internal functions |
| scalingMDS | All internal functions |
| setManyDatasets | All internal functions |
| simulationData | Simulation of Gaussian vector |
| smoothing.log | All internal functions |
| someErrorType | All internal functions |
| sortCPP | All internal functions |
| sortDataframe | All internal functions |
| sortMatrix | All internal functions |
| specClust | All internal functions |
| splitClusters | Split a cluster on the fly |
| splitVarCore | All internal functions |
| standardize | All internal functions |
| standardize_vect | All internal functions |
| strength_and_correlation | All internal functions |
| subsampleFile | All internal functions |
| summary.randomUniformForest | Random Uniform Forests for Classification, Regression and Unsupervised Learning |
| timer | All internal functions |
| timeStampCore | All internal functions |
| twoColumnsImportance | All internal functions |
| uniformDecisionTree | All internal functions |
| unsupervised | Unsupervised Learning with Random Uniform Forests |
| unsupervised.randomUniformForest | Unsupervised Learning with Random Uniform Forests |
| unsupervised2supervised | All internal functions |
| update | Update Unsupervised Learning object |
| update.unsupervised | Update Unsupervised Learning object |
| updateCombined.unsupervised | All internal functions |
| variance | All internal functions |
| vector2factor | All internal functions |
| vector2matrix | All internal functions |
| weightedVote | All internal functions |
| weightedVoteModel | All internal functions |
| which.is.duplicate | All internal functions |
| which.is.factor | All internal functions |
| which.is.na | All internal functions |
| which.is.nearestCenter | All internal functions |
| which.is.wholenumber | All internal functions |
| wineQualityRed | Wine Quality Data Set |
| XMinMaxCPP | All internal functions |