API for randomUniformForest
Random Uniform Forests for Classification, Regression and Unsupervised Learning

Global functions
CheckSameValuesInAllAttributes Source code
CheckSameValuesInAllAttributes} \alias{CheckSameValuesInLabels} Man page
CheckSameValuesInLabels Source code
ConcreteCompressiveStrength Man page
HuberDist Source code
Id Source code
L1Dist Source code
L1InformationGainCPP} \alias{L2.logDist} \alias{L2Dist} \alias{L Man page
L2.logDist Source code
L2Dist Source code
MDSscale Source code
MDSscale} \alias{mergeOutliers} \alias{unsupervised2supervised} Man page
NAFeatures Source code
NATreatment Source code
NAfactor2matrix Source code
NAfactor2matrix} \alias{OOBquantiles} \alias{XMinMaxCPP} \alias{ Man page
OOBquantiles Source code
as.supervised Man page Source code
as.true.matrix Source code
autoMPG Man page
bCI Man page Source code
bCICore Source code
biasVarCov Man page Source code
binomialrequiredSampleSize Source code
breastCancer Man page
carEvaluation Man page
classifyMatrixCPP} \alias{combineRUFObjects} \alias{concat} \ali Man page
clusterAnalysis Man page Source code
clusteringObservations Man page Source code
combineRUFObjects Source code
combineUnsupervised Man page Source code
concat Source code
concatCore Source code
confusion.matrix Source code
count.factor Source code
dates2numeric Man page Source code
define_train_test_sets Source code
difflog Source code
dummy.recode Source code
estimatePredictionAccuracy Source code
estimaterequiredSampleSize Source code
expectedSquaredBias Source code
extractYFromData Source code
fScore Source code
factor2matrix Source code
factor2vector Source code
fillNA2.randomUniformForest Man page Source code
fillVariablesNames Source code
fillWith Source code
filter.forest Source code
filter.object Source code
filterOutliers Man page Source code
find.first.idx Source code
find.idx Source code
find.root Source code
fullNode Source code
gMean Source code
gap.stats Source code
generalization.error Source code
generic.cv Man page Source code
generic.log Source code
generic.smoothing.log Source code
genericCbind Source code
genericNode Source code
genericOutput Source code
getCorr Source code
getOddEven Source code
getTree Man page
getTree.randomUniformForest Man page Source code
getVotesProbability Source code
getVotesProbability2 Source code
hClust Source code
importance Man page Source code
importance.randomUniformForest Man page Source code
inDummies Source code
init_values Man page Source code
insert.in.vector Source code
insert.in.vector2 Source code
insert.in.vector} \alias{insert.in.vector2} \alias{is.wholenumbe Man page
interClassesVariance Source code
intraClassesVariance Source code
is.wholenumber Source code
kBiggestProximities Source code
kMeans Source code
keep.index Source code
lagFunction Source code
leafNode Source code
leafNode} \alias{localTreeImportance} \alias{localVariableImport Man page
localTreeImportance Source code
localVariableImportance Source code
majorityClass Source code
matrix2factor Source code
matrix2factor2 Source code
mergeClusters Man page Source code
mergeLists Source code
mergeOutliers Source code
min_or_max Source code
modX Source code
model.stats Man page Source code
modifyClusters Man page Source code
monitorOOBError Source code
myAUC Source code
na.impute Source code
na.missing Source code
na.replace Source code
observationsImportance Source code
onlineClassify Source code
onlineCombineRUF Source code
optimizeFalsePositives Source code
options.filter Source code
outputPerturbationSampling Source code
outsideConfIntLevels Source code
overSampling Source code
parallelNA.replace Source code
partialDependenceBetweenPredictors Man page Source code
partialDependenceOverResponses Man page Source code
partialImportance Man page Source code
permuteCatValues Source code
perspWithcol Man page Source code
plot.importance Man page Source code
plot.randomUniformForest Man page Source code
plot.unsupervised Man page Source code
plotTree Man page Source code
plotTreeCore Source code
plotTreeCore2 Source code
plotTreeCore} \alias{plotTreeCore2} \alias{predictDecisionTree} Man page
postProcessingVotes Man page Source code
predict Man page
predict.randomUniformForest Man page Source code
predictDecisionTree Source code
predictionvsResponses Source code
print.importance Man page Source code
print.randomUniformForest Man page Source code
print.unsupervised Man page Source code
proximitiesMatrix Source code
pseudoHuberDist Source code
pseudoNAReplace Source code
rUniformForest.big Man page Source code
rUniformForest.combine Man page Source code
rUniformForest.grow Man page Source code
rUniformForest.merge Source code
rUniformForestPredict Source code
randomCombination Source code
randomUniformForest Man page Source code
randomUniformForest-package Man page
randomUniformForest.default Man page Source code
randomUniformForest.formula Man page Source code
randomUniformForestCore Source code
randomUniformForestCore.big Source code
randomUniformForestCore.merge Source code
randomUniformForestCore.predict Source code
randomUniformForestCore.predict} \alias{randomWhichMax} \alias{r Man page
randomUniformForestCore} \alias{randomUniformForestCore.big} \al Man page
randomWhichMax Source code
randomize Source code
rankingTrainData Source code
reSMOTE Man page Source code
reduce.trees Source code
residualsRandomUniformForest Source code
rewind.trees Source code
rm.InAList Source code
rm.coordinates Source code
rm.correlation Source code
rm.string Source code
rm.tempdir Source code
rm.trees Man page Source code
rmInAListByNames Source code
rmInf Source code
rmNA Man page Source code
rmNoise Source code
rmNoise} \alias{rollApplyFunction} \alias{runifMatrixCPP} \alias Man page
roc.curve Man page Source code
rollApplyFunction Source code
rufImpute Man page
scale2AnyValues Source code
scalingMDS Source code
setManyDatasets Source code
simulationData Man page Source code
smoothing.log Source code
someErrorType Source code
sortDataframe Source code
sortMatrix Source code
specClust Source code
specClust} \alias{rm.coordinates Man page
splitClusters Man page Source code
splitVarCore Source code
standardize Source code
standardize_vect Source code
standardize_vect} \alias{strength_and_correlation} \alias{subEst Man page
strength_and_correlation Source code
subEstimaterequiredSampleSize Source code
summary.randomUniformForest Man page Source code
timeStampCore Source code
timer Source code
twoColumnsImportance Source code
uniformDecisionTree Source code
uniformDecisionTree} \alias{vector2factor} \alias{vector2matrix} Man page
unsupervised Man page Source code
unsupervised.randomUniformForest Man page Source code
unsupervised2supervised Source code
update Man page
update.unsupervised Man page Source code
updateCombined.unsupervised Source code
variance Source code
vector2factor Source code
vector2matrix Source code
weightedVote Source code
weightedVoteModel Source code
which.is.duplicate Source code
which.is.duplicate} \alias{define_train_test_sets} \alias{difflo Man page
which.is.factor Source code
which.is.na Source code
which.is.nearestCenter Source code
which.is.nearestCenter} \alias{variance} \alias{interClassesVari Man page
which.is.wholenumber Source code
wineQualityRed Man page
randomUniformForest documentation built on May 29, 2017, 10:18 p.m.