GestureRecognitionToolkit  Version: 1.0 Revision: 04-03-15
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
GRT::RandomForests Member List

This is the complete list of members for GRT::RandomForests, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase)GRT::MLBase
baseType (defined in GRT::MLBase)GRT::MLBaseprotected
BaseTypes enum name (defined in GRT::MLBase)GRT::MLBase
bestDistance (defined in GRT::Classifier)GRT::Classifierprotected
classDistances (defined in GRT::Classifier)GRT::Classifierprotected
CLASSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
Classifier(void)GRT::Classifier
classifierMode (defined in GRT::Classifier)GRT::Classifierprotected
ClassifierModes enum name (defined in GRT::Classifier)GRT::Classifierprotected
classifierType (defined in GRT::Classifier)GRT::Classifierprotected
classLabels (defined in GRT::Classifier)GRT::Classifierprotected
classLikelihoods (defined in GRT::Classifier)GRT::Classifierprotected
classType (defined in GRT::GRTBase)GRT::GRTBaseprotected
clear()GRT::RandomForestsvirtual
CLUSTERER enum value (defined in GRT::MLBase)GRT::MLBase
copyBaseVariables(const Classifier *classifier)GRT::Classifier
copyGRTBaseVariables(const GRTBase *GRTBase)GRT::GRTBase
copyMLBaseVariables(const MLBase *mlBase)GRT::MLBase
createInstanceFromString(string const &classifierType)GRT::Classifierstatic
createNewInstance() const GRT::Classifier
debugLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
decisionTreeNode (defined in GRT::RandomForests)GRT::RandomForestsprotected
deepCopy() const GRT::Classifier
deepCopyDecisionTreeNode() const GRT::RandomForests
deepCopyFrom(const Classifier *classifier)GRT::RandomForestsvirtual
enableNullRejection(bool useNullRejection)GRT::Classifier
enableScaling(bool useScaling)GRT::MLBase
errorLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
forest (defined in GRT::RandomForests)GRT::RandomForestsprotected
forestSize (defined in GRT::RandomForests)GRT::RandomForestsprotected
getBaseClassifier() const GRT::Classifier
getBaseType() const GRT::MLBase
getBestDistance() const GRT::Classifier
getClassDistances() const GRT::Classifier
getClassifierPointer() const GRT::Classifier
getClassifierType() const GRT::Classifier
getClassLabelIndexValue(UINT classLabel) const GRT::Classifier
getClassLabels() const GRT::Classifier
getClassLikelihoods() const GRT::Classifier
getClassType() const GRT::GRTBase
getForest() const (defined in GRT::RandomForests)GRT::RandomForests
getForestSize() const GRT::RandomForests
getGRTBasePointer()GRT::GRTBase
getGRTBasePointer() const GRT::GRTBase
getGRTRevison()GRT::GRTBasestatic
getGRTVersion(bool returnRevision=true)GRT::GRTBasestatic
getIsBaseTypeClassifier() const GRT::MLBase
getIsBaseTypeClusterer() const GRT::MLBase
getIsBaseTypeRegressifier() const GRT::MLBase
getLastErrorMessage() const GRT::GRTBase
getLastInfoMessage() const GRT::GRTBase
getLastWarningMessage() const GRT::GRTBase
getLearningRate() const GRT::MLBase
getMap() (defined in GRT::Classifier)GRT::Classifierinlineprotectedstatic
getMaxDepth() const GRT::RandomForests
getMaximumLikelihood() const GRT::Classifier
getMaxNumEpochs() const GRT::MLBase
getMinChange() const GRT::MLBase
getMinNumEpochs() const GRT::MLBase
getMinNumSamplesPerNode() const GRT::RandomForests
getMLBasePointer()GRT::MLBase
getMLBasePointer() const GRT::MLBase
getModel(ostream &stream) const GRT::MLBasevirtual
getModelAsString() const GRT::MLBasevirtual
getModelTrained() const GRT::MLBase
getNullRejectionCoeff() const GRT::Classifier
getNullRejectionEnabled() const GRT::Classifier
getNullRejectionThresholds() const GRT::Classifier
getNumClasses() const GRT::Classifiervirtual
getNumInputDimensions() const GRT::MLBase
getNumInputFeatures() const GRT::MLBase
getNumOutputDimensions() const GRT::MLBase
getNumRandomSplits() const GRT::RandomForests
getNumTrainingIterationsToConverge() const GRT::MLBase
getPhase() const GRT::Classifier
getPredictedClassLabel() const GRT::Classifier
getRandomiseTrainingOrder() const GRT::MLBase
getRanges() const GRT::Classifier
getRegisteredClassifiers()GRT::Classifierstatic
getRemoveFeaturesAtEachSpilt() const GRT::RandomForests
getRootMeanSquaredTrainingError() const GRT::MLBase
getScalingEnabled() const GRT::MLBase
getSupportsNullRejection() const GRT::Classifier
getTimeseriesCompatible() const GRT::Classifierinline
getTotalSquaredTrainingError() const GRT::MLBase
getTrained() const GRT::MLBase
getTrainingMode() const GRT::RandomForests
getTrainingResults() const GRT::MLBase
getUseValidationSet() const GRT::MLBase
getValidationSetSize() const GRT::MLBase
GRTBase(void)GRT::GRTBase
infoLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
learningRate (defined in GRT::MLBase)GRT::MLBaseprotected
load(const string filename)GRT::MLBasevirtual
loadBaseSettingsFromFile(fstream &file)GRT::Classifierprotected
loadModelFromFile(fstream &file)GRT::RandomForestsvirtual
GRT::Classifier::loadModelFromFile(string filename)GRT::MLBasevirtual
map(VectorDouble inputVector)GRT::MLBasevirtual
map_(VectorDouble &inputVector)GRT::MLBasevirtual
maxDepth (defined in GRT::RandomForests)GRT::RandomForestsprotected
maxLikelihood (defined in GRT::Classifier)GRT::Classifierprotected
maxNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
minChange (defined in GRT::MLBase)GRT::MLBaseprotected
minNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
minNumSamplesPerNode (defined in GRT::RandomForests)GRT::RandomForestsprotected
MLBase(void)GRT::MLBase
notify(const TrainingResult &data) (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inlinevirtual
notify(const TestInstanceResult &data) (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inlinevirtual
notifyTestResultsObservers(const TestInstanceResult &data)GRT::MLBase
notifyTrainingResultsObservers(const TrainingResult &data)GRT::MLBase
nullRejectionCoeff (defined in GRT::Classifier)GRT::Classifierprotected
nullRejectionThresholds (defined in GRT::Classifier)GRT::Classifierprotected
numClasses (defined in GRT::Classifier)GRT::Classifierprotected
numInputDimensions (defined in GRT::MLBase)GRT::MLBaseprotected
numOutputDimensions (defined in GRT::MLBase)GRT::MLBaseprotected
numRandomSplits (defined in GRT::RandomForests)GRT::RandomForestsprotected
numTrainingIterationsToConverge (defined in GRT::MLBase)GRT::MLBaseprotected
Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inline
Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inline
operator=(const RandomForests &rhs)GRT::RandomForests
phase (defined in GRT::Classifier)GRT::Classifierprotected
predict(VectorDouble inputVector)GRT::MLBasevirtual
predict(MatrixDouble inputMatrix)GRT::MLBasevirtual
predict_(VectorDouble &inputVector)GRT::RandomForestsvirtual
GRT::Classifier::predict_(MatrixDouble &inputMatrix)GRT::MLBasevirtual
predictedClassLabel (defined in GRT::Classifier)GRT::Classifierprotected
print() const GRT::RandomForestsvirtual
random (defined in GRT::MLBase)GRT::MLBaseprotected
RandomForests(const DecisionTreeNode &decisionTreeNode=DecisionTreeClusterNode(), const UINT forestSize=10, const UINT numRandomSplits=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const UINT trainingMode=DecisionTree::BEST_RANDOM_SPLIT, const bool removeFeaturesAtEachSpilt=true, const bool useScaling=false)GRT::RandomForests
RandomForests(const RandomForests &rhs)GRT::RandomForests
randomiseTrainingOrder (defined in GRT::MLBase)GRT::MLBaseprotected
ranges (defined in GRT::Classifier)GRT::Classifierprotected
recomputeNullRejectionThresholds()GRT::Classifierinlinevirtual
registerTestResultsObserver(Observer< TestInstanceResult > &observer)GRT::MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)GRT::MLBase
REGRESSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
removeAllTestObservers()GRT::MLBase
removeAllTrainingObservers()GRT::MLBase
removeFeaturesAtEachSpilt (defined in GRT::RandomForests)GRT::RandomForestsprotected
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)GRT::MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)GRT::MLBase
reset()GRT::Classifiervirtual
rootMeanSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
save(const string filename) const GRT::MLBasevirtual
saveBaseSettingsToFile(fstream &file) const GRT::Classifierprotected
saveModelToFile(fstream &file) const GRT::RandomForestsvirtual
GRT::Classifier::saveModelToFile(string filename) const GRT::MLBasevirtual
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false)GRT::MLBaseinline
setDecisionTreeNode(const DecisionTreeNode &node)GRT::RandomForests
setForestSize(const UINT forestSize)GRT::RandomForests
setLearningRate(double learningRate)GRT::MLBase
setMaxDepth(const UINT maxDepth)GRT::RandomForests
setMaxNumEpochs(const UINT maxNumEpochs)GRT::MLBase
setMinChange(const double minChange)GRT::MLBase
setMinNumEpochs(const UINT minNumEpochs)GRT::MLBase
setMinNumSamplesPerNode(const UINT minNumSamplesPerNode)GRT::RandomForests
setNullRejectionCoeff(double nullRejectionCoeff)GRT::Classifiervirtual
setNullRejectionThresholds(VectorDouble newRejectionThresholds)GRT::Classifiervirtual
setNumRandomSplits(const UINT numSplittingSteps)GRT::RandomForests
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)GRT::MLBase
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt)GRT::RandomForests
setTrainingMode(const UINT trainingMode)GRT::RandomForests
setUseValidationSet(const bool useValidationSet)GRT::MLBase
setValidationSetSize(const UINT validationSetSize)GRT::MLBase
SQR(const double &x) const (defined in GRT::GRTBase)GRT::GRTBaseinlineprotected
STANDARD_CLASSIFIER_MODE enum value (defined in GRT::Classifier)GRT::Classifierprotected
StringClassifierMap typedefGRT::Classifier
supportsNullRejection (defined in GRT::Classifier)GRT::Classifierprotected
testingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
testResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
TIMESERIES_CLASSIFIER_MODE enum value (defined in GRT::Classifier)GRT::Classifierprotected
totalSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
train(ClassificationData trainingData)GRT::MLBasevirtual
train(RegressionData trainingData)GRT::MLBasevirtual
train(TimeSeriesClassificationData trainingData)GRT::MLBasevirtual
train(TimeSeriesClassificationDataStream trainingData)GRT::MLBasevirtual
train(UnlabelledData trainingData)GRT::MLBasevirtual
train(MatrixDouble data)GRT::MLBasevirtual
train_(ClassificationData &trainingData)GRT::RandomForestsvirtual
GRT::Classifier::train_(RegressionData &trainingData)GRT::MLBasevirtual
GRT::Classifier::train_(TimeSeriesClassificationData &trainingData)GRT::MLBasevirtual
GRT::Classifier::train_(TimeSeriesClassificationDataStream &trainingData)GRT::MLBasevirtual
GRT::Classifier::train_(UnlabelledData &trainingData)GRT::MLBasevirtual
GRT::Classifier::train_(MatrixDouble &data)GRT::MLBasevirtual
trained (defined in GRT::MLBase)GRT::MLBaseprotected
trainingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
trainingMode (defined in GRT::RandomForests)GRT::RandomForestsprotected
trainingResults (defined in GRT::MLBase)GRT::MLBaseprotected
trainingResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
useNullRejection (defined in GRT::Classifier)GRT::Classifierprotected
useScaling (defined in GRT::MLBase)GRT::MLBaseprotected
useValidationSet (defined in GRT::MLBase)GRT::MLBaseprotected
validationSetSize (defined in GRT::MLBase)GRT::MLBaseprotected
warningLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
~Classifier(void)GRT::Classifiervirtual
~GRTBase(void)GRT::GRTBasevirtual
~MLBase(void)GRT::MLBasevirtual
~Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inlinevirtual
~Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inlinevirtual
~RandomForests(void)GRT::RandomForestsvirtual