GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
ClusterTree Member List

This is the complete list of members for ClusterTree, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
BaseTypes enum name (defined in MLBase)MLBase
BEST_ITERATIVE_SPILT enum value (defined in Tree)Tree
BEST_RANDOM_SPLIT enum value (defined in Tree)Tree
bestDistance (defined in Clusterer)Clustererprotected
buildTree(const MatrixFloat &trainingData, ClusterTreeNode *parent, Vector< UINT > features, UINT &clusterLabel, UINT nodeID) (defined in ClusterTree)ClusterTreeprotected
CLASSIFIER enum value (defined in MLBase)MLBase
classType (defined in GRTBase)GRTBaseprotected
classType (defined in GRTBase)GRTBaseprotected
clear()ClusterTreevirtual
clusterDistances (defined in Clusterer)Clustererprotected
CLUSTERER enum value (defined in MLBase)MLBase
Clusterer(void)Clusterer
clustererType (defined in Clusterer)Clustererprotected
clusterLabels (defined in Clusterer)Clustererprotected
clusterLikelihoods (defined in Clusterer)Clustererprotected
ClusterTree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const UINT trainingMode=BEST_ITERATIVE_SPILT, const bool useScaling=false, const Float minRMSErrorPerNode=0.01)ClusterTree
ClusterTree(const ClusterTree &rhs)ClusterTree
computeBestSpilt(const MatrixFloat &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in ClusterTree)ClusterTreeprotected
computeBestSpiltBestIterativeSpilt(const MatrixFloat &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in ClusterTree)ClusterTreeprotected
computeBestSpiltBestRandomSpilt(const MatrixFloat &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in ClusterTree)ClusterTreeprotected
converged (defined in Clusterer)Clustererprotected
copyBaseVariables(const Clusterer *clusterer)Clusterer
Tree::copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
Clusterer::copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
createInstanceFromString(std::string const &ClustererType)Clustererstatic
createNewInstance() const Clusterer
debugLog (defined in GRTBase)GRTBaseprotected
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Clusterer
deepCopyFrom(const Clusterer *cluster)ClusterTreevirtual
deepCopyTree() const ClusterTreevirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
errorLog (defined in GRTBase)GRTBaseprotected
getBaseClusterer() const Clusterer
getBaseType() const MLBase
getBestDistance() const Clusterer
Tree::getClassType() const GRTBase
Clusterer::getClassType() const GRTBase
getClusterDistances() const Clusterer
getClustererType() const Clusterer
getClusterLabels() const Clusterer
getClusterLikelihoods() const Clusterer
getConverged() const Clusterer
Tree::getGRTBasePointer()GRTBase
Tree::getGRTBasePointer() const GRTBase
Clusterer::getGRTBasePointer()GRTBase
Clusterer::getGRTBasePointer() const GRTBase
Tree::getGRTRevison()GRTBasestatic
Clusterer::getGRTRevison()GRTBasestatic
Tree::getGRTVersion(bool returnRevision=true)GRTBasestatic
Clusterer::getGRTVersion(bool returnRevision=true)GRTBasestatic
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
Tree::getLastErrorMessage() const GRTBase
Clusterer::getLastErrorMessage() const GRTBase
Tree::getLastInfoMessage() const GRTBase
Clusterer::getLastInfoMessage() const GRTBase
Tree::getLastWarningMessage() const GRTBase
Clusterer::getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMap() (defined in Clusterer)Clustererinlineprotectedstatic
getMaxDepth() const Tree
getMaximumLikelihood() const Clusterer
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMinNumSamplesPerNode() const Tree
getMinRMSErrorPerNode() const ClusterTree
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
Tree::getModel(std::ostream &stream) const Treevirtual
Clusterer::getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getModelTrained() const MLBase
getNumClusters() const Clusterer
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumSplittingSteps() const Tree
getNumTrainingIterationsToConverge() const MLBase
getOutputType() const MLBase
getPredictedClusterLabel() const ClusterTree
getPredictedNodeID() const Tree
getRandomiseTrainingOrder() const MLBase
getRegisteredClusterers()Clustererstatic
getRemoveFeaturesAtEachSpilt() const Tree
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingMode() const Tree
getTrainingResults() const MLBase
getTree() const ClusterTree
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::string filename) is deprecated, use save(std::string filename) instead", virtual bool saveModelToFile(std::string filename) const )MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::string filename) is deprecated, use load(std::string filename) instead", virtual bool loadModelFromFile(std::string filename))MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))MLBase
Tree::GRTBase(void)GRTBase
Clusterer::GRTBase(void)GRTBase
infoLog (defined in GRTBase)GRTBaseprotected
infoLog (defined in GRTBase)GRTBaseprotected
inputType (defined in MLBase)MLBaseprotected
learningRate (defined in MLBase)MLBaseprotected
load(const std::string filename)MLBasevirtual
load(std::fstream &file)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)MLBaseprotected
loadClustererSettingsFromFile(std::fstream &file)Clustererprotected
loadModelFromFile(std::fstream &file)ClusterTreevirtual
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxDepth (defined in Tree)Treeprotected
maxLikelihood (defined in Clusterer)Clustererprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
minNumSamplesPerNode (defined in Tree)Treeprotected
minRMSErrorPerNode (defined in ClusterTree)ClusterTreeprotected
MLBase(void)MLBase
notify(const TrainingResult &data) (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
notify(const TestInstanceResult &data) (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
notifyTestResultsObservers(const TestInstanceResult &data)MLBase
notifyTrainingResultsObservers(const TrainingResult &data)MLBase
NUM_TRAINING_MODES enum value (defined in Tree)Tree
numClustersClustererprotected
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numSplittingSteps (defined in Tree)Treeprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
operator=(const ClusterTree &rhs)ClusterTree
outputType (defined in MLBase)MLBaseprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)ClusterTreevirtual
Clusterer::predict_(MatrixFloat &inputMatrix)MLBasevirtual
predictedClusterLabelClustererprotected
print() const ClusterTreevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
ranges (defined in Clusterer)Clustererprotected
registerModule (defined in ClusterTree)ClusterTreeprotectedstatic
registerTestResultsObserver(Observer< TestInstanceResult > &observer)MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)MLBase
REGRESSIFIER enum value (defined in MLBase)MLBase
removeAllTestObservers()MLBase
removeAllTrainingObservers()MLBase
removeFeaturesAtEachSpilt (defined in Tree)Treeprotected
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)MLBase
reset()Clusterervirtual
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(const std::string filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
saveClustererSettingsToFile(std::fstream &file) const Clustererprotected
saveModelToFile(std::fstream &file) const ClusterTreevirtual
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)MLBaseinline
Tree::setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
Clusterer::setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
Tree::setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
Clusterer::setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
setLearningRate(const Float learningRate)MLBase
setMaxDepth(const UINT maxDepth)Tree
setMaxNumEpochs(const UINT maxNumEpochs)MLBase
setMinChange(const Float minChange)MLBase
setMinNumEpochs(const UINT minNumEpochs)MLBase
setMinNumSamplesPerNode(const UINT minNumSamplesPerNode)Tree
setMinRMSErrorPerNode(const Float minRMSErrorPerNode)ClusterTree
setNumClusters(const UINT numClusters)Clusterer
setNumSplittingSteps(const UINT numSplittingSteps)Tree
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt)Tree
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingMode(const UINT trainingMode)Tree
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
Tree::setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
Clusterer::setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
StringClustererMap typedefClusterer
testingLog (defined in GRTBase)GRTBaseprotected
testingLog (defined in GRTBase)GRTBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(TimeSeriesClassificationData trainingData)MLBasevirtual
train(ClassificationDataStream trainingData)MLBasevirtual
train(UnlabelledData trainingData)MLBasevirtual
train(MatrixFloat data)MLBasevirtual
train_(MatrixFloat &trainingData)ClusterTreevirtual
Clusterer::train_(ClassificationData &trainingData)Clusterervirtual
Clusterer::train_(UnlabelledData &trainingData)Clusterervirtual
MLBase::train_(RegressionData &trainingData)MLBasevirtual
MLBase::train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
MLBase::train_(ClassificationDataStream &trainingData)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
TrainingMode enum name (defined in Tree)Tree
trainingMode (defined in Tree)Treeprotected
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
tree (defined in Tree)Treeprotected
Tree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const UINT trainingMode=BEST_ITERATIVE_SPILT)Tree
useScaling (defined in MLBase)MLBaseprotected
useValidationSet (defined in MLBase)MLBaseprotected
validationSetAccuracy (defined in MLBase)MLBaseprotected
validationSetPrecision (defined in MLBase)MLBaseprotected
validationSetRecall (defined in MLBase)MLBaseprotected
validationSetSize (defined in MLBase)MLBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
~Clusterer(void)Clusterervirtual
~ClusterTree(void)ClusterTreevirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
~Tree(void)Treevirtual