GestureRecognitionToolkit  Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
Tree Member List

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

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
BaseType enum name (defined in MLBase)MLBase
batchSize (defined in MLBase)MLBaseprotected
BEST_ITERATIVE_SPILT enum value (defined in Tree)Tree
BEST_RANDOM_SPLIT enum value (defined in Tree)Tree
classIdGRTBaseprotected
CLASSIFIER enum value (defined in MLBase)MLBase
clear() overrideTreevirtual
CLUSTERER enum value (defined in MLBase)MLBase
CONTEXT enum value (defined in MLBase)MLBase
converged (defined in MLBase)MLBaseprotected
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
debugLog (defined in GRTBase)GRTBaseprotected
deepCopyTree() const Treevirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
FEATURE_EXTRACTION enum value (defined in MLBase)MLBase
getBatchSize() const MLBase
getConverged() const MLBase
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
getId() const GRTBase
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
getLastErrorMessage() const GRTBase
getLastInfoMessage() const GRTBase
getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMaxDepth() const Tree
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMinNumSamplesPerNode() const Tree
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const overrideTreevirtual
getModelAsString() const MLBasevirtual
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumRestarts() const MLBase
getNumSplittingSteps() const Tree
getNumTrainingIterationsToConverge() const MLBase
getOutputType() const MLBase
getPredictedNodeID() const Tree
getRandomiseTrainingOrder() const MLBase
getRemoveFeaturesAtEachSpilt() const Tree
getRMSTrainingError() const MLBase
getRMSValidationError() const MLBase
getScalingEnabled() const MLBase
getTestingLoggingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingLoggingEnabled() const MLBase
getTrainingMode() const Tree
getTrainingResults() const MLBase
getTree() const Tree
getType() const MLBase
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(const std::string &filename) instead", virtual bool saveModelToFile(const 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(const std::string &filename) instead", virtual bool loadModelFromFile(const 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
GRT_DEPRECATED_MSG("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )MLBase
GRT_DEPRECATED_MSG("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const )MLBase
GRTBase::GRT_DEPRECATED_MSG("getClassType is deprecated, use getId() instead!", std::string getClassType() const )GRTBase
GRTBase(const std::string &id="")GRTBase
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
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxDepth (defined in Tree)Treeprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
minNumSamplesPerNode (defined in Tree)Treeprotected
MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)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
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numRestarts (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
outputType (defined in MLBase)MLBaseprotected
POST_PROCESSING enum value (defined in MLBase)MLBase
PRE_PROCSSING enum value (defined in MLBase)MLBase
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)MLBasevirtual
predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const overrideTreevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
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()MLBasevirtual
rmsTrainingError (defined in MLBase)MLBaseprotected
rmsValidationError (defined in MLBase)MLBaseprotected
save(const std::string &filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)GRTBaseinline
setBatchSize(const UINT batchSize)MLBase
setDebugLoggingEnabled(const bool loggingEnabled)GRTBase
setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
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
setNumRestarts(const UINT numRestarts)MLBase
setNumSplittingSteps(const UINT numSplittingSteps)Tree
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt)Tree
setTestingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingMode(const TrainingMode trainingMode)Tree
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
SQR(const Float &x) const (defined in GRTBase)GRTBaseinline
testingLog (defined in MLBase)MLBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(RegressionData trainingData, RegressionData validationData)MLBasevirtual
train(TimeSeriesClassificationData trainingData)MLBasevirtual
train(ClassificationDataStream trainingData)MLBasevirtual
train(UnlabelledData trainingData)MLBasevirtual
train(MatrixFloat data)MLBasevirtual
train_(ClassificationData &trainingData)MLBasevirtual
train_(RegressionData &trainingData)MLBasevirtual
train_(RegressionData &trainingData, RegressionData &validationData)MLBasevirtual
train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
train_(ClassificationDataStream &trainingData)MLBasevirtual
train_(UnlabelledData &trainingData)MLBasevirtual
train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in MLBase)MLBaseprotected
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 TrainingMode 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
~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