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 |