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.
RegressionTree Member List

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

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
BaseType enum name (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
batchSize (defined in MLBase)MLBaseprotected
buildTree(const RegressionData &trainingData, RegressionTreeNode *parent, Vector< UINT > features, UINT nodeID) (defined in RegressionTree)RegressionTreeprotected
classIdGRTBaseprotected
CLASSIFIER enum value (defined in MLBase)MLBase
clear() overrideRegressionTreevirtual
CLUSTERER enum value (defined in MLBase)MLBase
computeBestSpilt(const RegressionData &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in RegressionTree)RegressionTreeprotected
computeBestSpiltBestIterativeSpilt(const RegressionData &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in RegressionTree)RegressionTreeprotected
computeNodeRegressionData(const RegressionData &trainingData, VectorFloat &regressionData) (defined in RegressionTree)RegressionTreeprotected
CONTEXT enum value (defined in MLBase)MLBase
converged (defined in MLBase)MLBaseprotected
copyBaseVariables(const Regressifier *regressifier)Regressifier
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
create(const std::string &id)Regressifierstatic
create() const Regressifier
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Regressifier
deepCopyFrom(const Regressifier *regressifier) overrideRegressionTreevirtual
deepCopyTree() const RegressionTree
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
FEATURE_EXTRACTION enum value (defined in MLBase)MLBase
getBaseRegressifier() const Regressifier
getBatchSize() const MLBase
getConverged() const MLBase
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
getId()RegressionTreestatic
Regressifier::getId() const GRTBase
getInputRanges() const Regressifier
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
getLastErrorMessage() const GRTBase
getLastInfoMessage() const GRTBase
getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMap() (defined in Regressifier)Regressifierinlineprotectedstatic
getMaxDepth() const RegressionTree
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMinNumSamplesPerNode() const RegressionTree
getMinRMSErrorPerNode() const RegressionTree
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumRestarts() const MLBase
getNumSplittingSteps() const RegressionTree
getNumTrainingIterationsToConverge() const MLBase
getOutputRanges() const Regressifier
getOutputType() const MLBase
getPredictedNodeID() const RegressionTree
getRandomiseTrainingOrder() const MLBase
getRegisteredRegressifiers()Regressifierstatic
getRegressionData() const Regressifier
getRemoveFeaturesAtEachSpilt() const RegressionTree
getRMSTrainingError() const MLBase
getRMSValidationError() const MLBase
getScalingEnabled() const MLBase
getTestingLoggingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingLoggingEnabled() const MLBase
getTrainingMode() const RegressionTree
getTrainingResults() const MLBase
getTree() const RegressionTree
getType() const MLBase
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
GRT_DEPRECATED_MSG("createNewInstance is deprecated, use create() instead.", Regressifier *createNewInstance() const ) (defined in Regressifier)Regressifier
GRT_DEPRECATED_MSG("createInstanceFromString(id) is deprecated, use create(id) instead.", static Regressifier *createInstanceFromString(const std::string &id)) (defined in Regressifier)Regressifier
GRT_DEPRECATED_MSG("getRegressifierType is deprecated, use getId() instead", std::string getRegressifierType() const ) (defined in Regressifier)Regressifier
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
MLBase::GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )MLBase
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
MLBase::GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))MLBase
MLBase::GRT_DEPRECATED_MSG("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )MLBase
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
inputVectorRanges (defined in Regressifier)Regressifierprotected
learningRate (defined in MLBase)MLBaseprotected
load(std::fstream &file) overrideRegressionTreevirtual
Regressifier::load(const std::string &filename)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)Regressifierprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxDepth (defined in RegressionTree)RegressionTreeprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
minNumSamplesPerNode (defined in RegressionTree)RegressionTreeprotected
minRMSErrorPerNode (defined in RegressionTree)RegressionTreeprotected
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
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numRestarts (defined in MLBase)MLBaseprotected
numSplittingSteps (defined in RegressionTree)RegressionTreeprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
operator=(const RegressionTree &rhs)RegressionTree
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) overrideRegressionTreevirtual
Regressifier::predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const overrideRegressionTreevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
registerTestResultsObserver(Observer< TestInstanceResult > &observer)MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)MLBase
Regressifier(const std::string &id="")Regressifier
REGRESSIFIER enum value (defined in MLBase)MLBase
regressifierType (defined in Regressifier)Regressifierprotected
regressionData (defined in Regressifier)Regressifierprotected
RegressionTree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const Tree::TrainingMode trainingMode=Tree::BEST_ITERATIVE_SPILT, const bool useScaling=false, const Float minRMSErrorPerNode=0.01)RegressionTree
RegressionTree(const RegressionTree &rhs)RegressionTree
removeAllTestObservers()MLBase
removeAllTrainingObservers()MLBase
removeFeaturesAtEachSpilt (defined in RegressionTree)RegressionTreeprotected
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)MLBase
reset() overrideRegressifiervirtual
rmsTrainingError (defined in MLBase)MLBaseprotected
rmsValidationError (defined in MLBase)MLBaseprotected
save(std::fstream &file) const overrideRegressionTreevirtual
Regressifier::save(const std::string &filename) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const Regressifierprotected
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)RegressionTree
setMaxNumEpochs(const UINT maxNumEpochs)MLBase
setMinChange(const Float minChange)MLBase
setMinNumEpochs(const UINT minNumEpochs)MLBase
setMinNumSamplesPerNode(const UINT minNumSamplesPerNode)RegressionTree
setMinRMSErrorPerNode(const Float minRMSErrorPerNode)RegressionTree
setNumRestarts(const UINT numRestarts)MLBase
setNumSplittingSteps(const UINT numSplittingSteps)RegressionTree
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt)RegressionTree
setTestingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingMode(const Tree::TrainingMode trainingMode)RegressionTree
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
SQR(const Float &x) const (defined in GRTBase)GRTBaseinline
StringRegressifierMap typedefRegressifier
targetVectorRanges (defined in Regressifier)Regressifierprotected
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_(RegressionData &trainingData) overrideRegressionTreevirtual
Regressifier::train_(ClassificationData &trainingData)MLBasevirtual
Regressifier::train_(RegressionData &trainingData, RegressionData &validationData)MLBasevirtual
Regressifier::train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
Regressifier::train_(ClassificationDataStream &trainingData)MLBasevirtual
Regressifier::train_(UnlabelledData &trainingData)MLBasevirtual
Regressifier::train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in MLBase)MLBaseprotected
trainingMode (defined in RegressionTree)RegressionTreeprotected
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
treeRegressionTreeprotected
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
~Regressifier(void)Regressifiervirtual
~RegressionTree(void)RegressionTreevirtual