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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.
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This is the complete list of members for GRT::Regressifier, 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 | |
CLASSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
classType (defined in GRT::GRTBase) | GRT::GRTBase | protected |
clear() | GRT::Regressifier | virtual |
CLUSTERER enum value (defined in GRT::MLBase) | GRT::MLBase | |
copyBaseVariables(const Regressifier *regressifier) | 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 |
deepCopy() const | GRT::Regressifier | |
deepCopyFrom(const Regressifier *regressifier) | GRT::Regressifier | inlinevirtual |
enableScaling(bool useScaling) | GRT::MLBase | |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
getBaseRegressifier() const | GRT::Regressifier | |
getBaseType() const | GRT::MLBase | |
getClassType() const | GRT::GRTBase | |
getGRTBasePointer() | GRT::GRTBase | |
getGRTBasePointer() const | GRT::GRTBase | |
getGRTRevison() | GRT::GRTBase | static |
getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
getInputRanges() const | GRT::Regressifier | |
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::Regressifier) | GRT::Regressifier | inlineprotectedstatic |
getMaxNumEpochs() const | GRT::MLBase | |
getMinChange() const | GRT::MLBase | |
getMinNumEpochs() const | GRT::MLBase | |
getMLBasePointer() | GRT::MLBase | |
getMLBasePointer() const | GRT::MLBase | |
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 | |
getNumTrainingIterationsToConverge() const | GRT::MLBase | |
getOutputRanges() const | GRT::Regressifier | |
getRandomiseTrainingOrder() const | GRT::MLBase | |
getRegisteredRegressifiers() | GRT::Regressifier | static |
getRegressifierType() const | GRT::Regressifier | |
getRegressionData() const | GRT::Regressifier | |
getRootMeanSquaredTrainingError() const | GRT::MLBase | |
getScalingEnabled() const | GRT::MLBase | |
getTotalSquaredTrainingError() const | GRT::MLBase | |
getTrained() const | GRT::MLBase | |
getTrainingResults() const | GRT::MLBase | |
getUseValidationSet() const | GRT::MLBase | |
getValidationSetSize() const | GRT::MLBase | |
GRTBase(void) | GRT::GRTBase | |
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(string filename) | GRT::MLBase | virtual |
loadModelFromFile(fstream &file) | GRT::MLBase | virtual |
map(VectorDouble inputVector) | GRT::MLBase | virtual |
map_(VectorDouble &inputVector) | GRT::MLBase | virtual |
maxNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
minChange (defined in GRT::MLBase) | GRT::MLBase | protected |
minNumEpochs (defined in GRT::MLBase) | GRT::MLBase | 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 | |
numInputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | 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 |
predict(VectorDouble inputVector) | GRT::MLBase | virtual |
predict(MatrixDouble inputMatrix) | GRT::MLBase | virtual |
predict_(VectorDouble &inputVector) | GRT::MLBase | virtual |
predict_(MatrixDouble &inputMatrix) | GRT::MLBase | virtual |
print() const | GRT::MLBase | virtual |
random (defined in GRT::MLBase) | GRT::MLBase | protected |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | protected |
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 |
removeAllTestObservers() | GRT::MLBase | |
removeAllTrainingObservers() | GRT::MLBase | |
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(string filename) const | GRT::MLBase | virtual |
saveModelToFile(fstream &file) 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 | |
setMaxNumEpochs(const UINT maxNumEpochs) | GRT::MLBase | |
setMinChange(const double minChange) | GRT::MLBase | |
setMinNumEpochs(const UINT minNumEpochs) | GRT::MLBase | |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | GRT::MLBase | |
setUseValidationSet(const bool useValidationSet) | GRT::MLBase | |
setValidationSetSize(const UINT validationSetSize) | GRT::MLBase | |
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 |
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_(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 |
trained (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
trainingResults (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
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 |
~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 |