![]() |
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.
|
This is the complete list of members for GRT::RegressionTree, including all inherited members.
BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase) | GRT::MLBase | |
baseType (defined in GRT::MLBase) | GRT::MLBase | protected |
BaseTypes enum name (defined in GRT::MLBase) | GRT::MLBase | |
BEST_ITERATIVE_SPILT enum value (defined in GRT::Tree) | GRT::Tree | |
BEST_RANDOM_SPLIT enum value (defined in GRT::Tree) | GRT::Tree | |
buildTree(const RegressionData &trainingData, RegressionTreeNode *parent, vector< UINT > features, UINT nodeID) (defined in GRT::RegressionTree) | GRT::RegressionTree | protected |
CLASSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
classType (defined in GRT::GRTBase) | GRT::GRTBase | protected |
classType (defined in GRT::GRTBase) | GRT::GRTBase | protected |
clear() | GRT::RegressionTree | virtual |
CLUSTERER enum value (defined in GRT::MLBase) | GRT::MLBase | |
computeBestSpilt(const RegressionData &trainingData, const vector< UINT > &features, UINT &featureIndex, double &threshold, double &minError) (defined in GRT::RegressionTree) | GRT::RegressionTree | protected |
computeBestSpiltBestIterativeSpilt(const RegressionData &trainingData, const vector< UINT > &features, UINT &featureIndex, double &threshold, double &minError) (defined in GRT::RegressionTree) | GRT::RegressionTree | protected |
computeNodeRegressionData(const RegressionData &trainingData, VectorDouble ®ressionData) (defined in GRT::RegressionTree) | GRT::RegressionTree | protected |
copyBaseVariables(const Regressifier *regressifier) | GRT::Regressifier | |
GRT::copyGRTBaseVariables(const GRTBase *GRTBase) | GRT::GRTBase | |
GRT::Regressifier::copyGRTBaseVariables(const GRTBase *GRTBase) | GRT::GRTBase | |
copyMLBaseVariables(const MLBase *mlBase) | GRT::MLBase | |
createInstanceFromString(string const ®ressifierType) | GRT::Regressifier | static |
createNewInstance() const | GRT::Regressifier | |
debugLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
debugLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
deepCopy() const | GRT::Regressifier | |
deepCopyFrom(const Regressifier *regressifier) | GRT::RegressionTree | virtual |
deepCopyTree() const | GRT::RegressionTree | virtual |
enableScaling(bool useScaling) | GRT::MLBase | |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
getBaseRegressifier() const | GRT::Regressifier | |
getBaseType() const | GRT::MLBase | |
GRT::getClassType() const | GRT::GRTBase | |
GRT::Regressifier::getClassType() const | GRT::GRTBase | |
GRT::getGRTBasePointer() | GRT::GRTBase | |
GRT::getGRTBasePointer() const | GRT::GRTBase | |
GRT::Regressifier::getGRTBasePointer() | GRT::GRTBase | |
GRT::Regressifier::getGRTBasePointer() const | GRT::GRTBase | |
GRT::getGRTRevison() | GRT::GRTBase | static |
GRT::Regressifier::getGRTRevison() | GRT::GRTBase | static |
GRT::getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
GRT::Regressifier::getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
getInputRanges() const | GRT::Regressifier | |
getIsBaseTypeClassifier() const | GRT::MLBase | |
getIsBaseTypeClusterer() const | GRT::MLBase | |
getIsBaseTypeRegressifier() const | GRT::MLBase | |
GRT::getLastErrorMessage() const | GRT::GRTBase | |
GRT::Regressifier::getLastErrorMessage() const | GRT::GRTBase | |
GRT::getLastInfoMessage() const | GRT::GRTBase | |
GRT::Regressifier::getLastInfoMessage() const | GRT::GRTBase | |
GRT::getLastWarningMessage() const | GRT::GRTBase | |
GRT::Regressifier::getLastWarningMessage() const | GRT::GRTBase | |
getLearningRate() const | GRT::MLBase | |
getMap() (defined in GRT::Regressifier) | GRT::Regressifier | inlineprotectedstatic |
getMaxDepth() const | GRT::Tree | |
getMaxNumEpochs() const | GRT::MLBase | |
getMinChange() const | GRT::MLBase | |
getMinNumEpochs() const | GRT::MLBase | |
getMinNumSamplesPerNode() const | GRT::Tree | |
getMinRMSErrorPerNode() const | GRT::RegressionTree | |
getMLBasePointer() | GRT::MLBase | |
getMLBasePointer() const | GRT::MLBase | |
GRT::getModel(ostream &stream) const | GRT::Tree | virtual |
GRT::Regressifier::getModel(ostream &stream) const | GRT::MLBase | virtual |
getModelAsString() const | GRT::MLBase | virtual |
getModelTrained() const | GRT::MLBase | |
getNumInputDimensions() const | GRT::MLBase | |
getNumInputFeatures() const | GRT::MLBase | |
getNumOutputDimensions() const | GRT::MLBase | |
getNumSplittingSteps() const | GRT::Tree | |
getNumTrainingIterationsToConverge() const | GRT::MLBase | |
getOutputRanges() const | GRT::Regressifier | |
getPredictedNodeID() const | GRT::Tree | |
getRandomiseTrainingOrder() const | GRT::MLBase | |
getRegisteredRegressifiers() | GRT::Regressifier | static |
getRegressifierType() const | GRT::Regressifier | |
getRegressionData() const | GRT::Regressifier | |
getRemoveFeaturesAtEachSpilt() const | GRT::Tree | |
getRootMeanSquaredTrainingError() const | GRT::MLBase | |
getScalingEnabled() const | GRT::MLBase | |
getTotalSquaredTrainingError() const | GRT::MLBase | |
getTrained() const | GRT::MLBase | |
getTrainingMode() const | GRT::Tree | |
getTrainingResults() const | GRT::MLBase | |
getTree() const | GRT::RegressionTree | |
getUseValidationSet() const | GRT::MLBase | |
getValidationSetSize() const | GRT::MLBase | |
GRT::GRTBase(void) | GRT::GRTBase | |
GRT::Regressifier::GRTBase(void) | GRT::GRTBase | |
infoLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
infoLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
inputVectorRanges (defined in GRT::Regressifier) | GRT::Regressifier | protected |
learningRate (defined in GRT::MLBase) | GRT::MLBase | protected |
load(const string filename) | GRT::MLBase | virtual |
loadBaseSettingsFromFile(fstream &file) | GRT::Regressifier | protected |
loadModelFromFile(fstream &file) | GRT::RegressionTree | virtual |
GRT::Regressifier::loadModelFromFile(string filename) | GRT::MLBase | virtual |
map(VectorDouble inputVector) | GRT::MLBase | virtual |
map_(VectorDouble &inputVector) | GRT::MLBase | virtual |
maxDepth (defined in GRT::Tree) | GRT::Tree | protected |
maxNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
minChange (defined in GRT::MLBase) | GRT::MLBase | protected |
minNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
minNumSamplesPerNode (defined in GRT::Tree) | GRT::Tree | protected |
minRMSErrorPerNode | GRT::RegressionTree | protected |
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 | |
NUM_TRAINING_MODES enum value (defined in GRT::Tree) | GRT::Tree | |
numInputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numSplittingSteps (defined in GRT::Tree) | GRT::Tree | protected |
numTrainingIterationsToConverge (defined in GRT::MLBase) | GRT::MLBase | protected |
Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inline |
Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inline |
operator=(const RegressionTree &rhs) | GRT::RegressionTree | |
predict(VectorDouble inputVector) | GRT::MLBase | virtual |
predict(MatrixDouble inputMatrix) | GRT::MLBase | virtual |
predict_(VectorDouble &inputVector) | GRT::RegressionTree | virtual |
GRT::Regressifier::predict_(MatrixDouble &inputMatrix) | GRT::MLBase | virtual |
print() const | GRT::RegressionTree | virtual |
random (defined in GRT::MLBase) | GRT::MLBase | protected |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | protected |
registerModule (defined in GRT::RegressionTree) | GRT::RegressionTree | protectedstatic |
registerTestResultsObserver(Observer< TestInstanceResult > &observer) | GRT::MLBase | |
registerTrainingResultsObserver(Observer< TrainingResult > &observer) | GRT::MLBase | |
Regressifier(void) | GRT::Regressifier | |
REGRESSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
regressifierType (defined in GRT::Regressifier) | GRT::Regressifier | protected |
regressionData (defined in GRT::Regressifier) | GRT::Regressifier | protected |
RegressionTree(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 double minRMSErrorPerNode=0.01) | GRT::RegressionTree | |
RegressionTree(const RegressionTree &rhs) | GRT::RegressionTree | |
removeAllTestObservers() | GRT::MLBase | |
removeAllTrainingObservers() | GRT::MLBase | |
removeFeaturesAtEachSpilt (defined in GRT::Tree) | GRT::Tree | protected |
removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | GRT::MLBase | |
removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | GRT::MLBase | |
reset() | GRT::Regressifier | virtual |
rootMeanSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
save(const string filename) const | GRT::MLBase | virtual |
saveBaseSettingsToFile(fstream &file) const | GRT::Regressifier | protected |
saveModelToFile(fstream &file) const | GRT::RegressionTree | virtual |
GRT::Regressifier::saveModelToFile(string filename) const | GRT::MLBase | virtual |
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false) | GRT::MLBase | inline |
setLearningRate(double learningRate) | GRT::MLBase | |
setMaxDepth(const UINT maxDepth) | GRT::Tree | |
setMaxNumEpochs(const UINT maxNumEpochs) | GRT::MLBase | |
setMinChange(const double minChange) | GRT::MLBase | |
setMinNumEpochs(const UINT minNumEpochs) | GRT::MLBase | |
setMinNumSamplesPerNode(const UINT minNumSamplesPerNode) | GRT::Tree | |
setMinRMSErrorPerNode(const double minRMSErrorPerNode) | GRT::RegressionTree | |
setNumSplittingSteps(const UINT numSplittingSteps) | GRT::Tree | |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | GRT::MLBase | |
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt) | GRT::Tree | |
setTrainingMode(const UINT trainingMode) | GRT::Tree | |
setUseValidationSet(const bool useValidationSet) | GRT::MLBase | |
setValidationSetSize(const UINT validationSetSize) | GRT::MLBase | |
SQR(const double &x) const (defined in GRT::GRTBase) | GRT::GRTBase | inlineprotected |
SQR(const double &x) const (defined in GRT::GRTBase) | GRT::GRTBase | inlineprotected |
StringRegressifierMap typedef | GRT::Regressifier | |
targetVectorRanges (defined in GRT::Regressifier) | GRT::Regressifier | protected |
testingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
testingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
testResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
totalSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
train(ClassificationData trainingData) | GRT::MLBase | virtual |
train(RegressionData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationDataStream trainingData) | GRT::MLBase | virtual |
train(UnlabelledData trainingData) | GRT::MLBase | virtual |
train(MatrixDouble data) | GRT::MLBase | virtual |
train_(RegressionData &trainingData) | GRT::RegressionTree | virtual |
GRT::Regressifier::train_(ClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::Regressifier::train_(TimeSeriesClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::Regressifier::train_(TimeSeriesClassificationDataStream &trainingData) | GRT::MLBase | virtual |
GRT::Regressifier::train_(UnlabelledData &trainingData) | GRT::MLBase | virtual |
GRT::Regressifier::train_(MatrixDouble &data) | GRT::MLBase | virtual |
trained (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
TrainingMode enum name (defined in GRT::Tree) | GRT::Tree | |
trainingMode (defined in GRT::Tree) | GRT::Tree | protected |
trainingResults (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
tree (defined in GRT::Tree) | GRT::Tree | protected |
Tree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const UINT trainingMode=BEST_ITERATIVE_SPILT) | GRT::Tree | |
useScaling (defined in GRT::MLBase) | GRT::MLBase | protected |
useValidationSet (defined in GRT::MLBase) | GRT::MLBase | protected |
validationSetSize (defined in GRT::MLBase) | GRT::MLBase | protected |
warningLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
warningLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
~GRTBase(void) | GRT::GRTBase | virtual |
~MLBase(void) | GRT::MLBase | virtual |
~Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlinevirtual |
~Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlinevirtual |
~Regressifier(void) | GRT::Regressifier | virtual |
~RegressionTree(void) | GRT::RegressionTree | virtual |
~Tree(void) | GRT::Tree | virtual |