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.
GRT::DiscreteHiddenMarkovModel Member List

This is the complete list of members for GRT::DiscreteHiddenMarkovModel, including all inherited members.

a (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
b (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase)GRT::MLBase
baseType (defined in GRT::MLBase)GRT::MLBaseprotected
BaseTypes enum name (defined in GRT::MLBase)GRT::MLBase
CLASSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
classType (defined in GRT::GRTBase)GRT::GRTBaseprotected
clear()GRT::MLBasevirtual
CLUSTERER enum value (defined in GRT::MLBase)GRT::MLBase
copyGRTBaseVariables(const GRTBase *GRTBase)GRT::GRTBase
copyMLBaseVariables(const MLBase *mlBase)GRT::MLBase
cThreshold (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
debugLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
delta (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
DiscreteHiddenMarkovModel() (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
DiscreteHiddenMarkovModel(const UINT numStates, const UINT numSymbols, const UINT modelType, const UINT delta) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
DiscreteHiddenMarkovModel(const MatrixDouble &a, const MatrixDouble &b, const VectorDouble &pi, const UINT modelType, const UINT delta) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
DiscreteHiddenMarkovModel(const DiscreteHiddenMarkovModel &rhs) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
enableScaling(bool useScaling)GRT::MLBase
errorLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
estimatedStates (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
forwardBackward(HMMTrainingObject &trainingObject, const vector< UINT > &obs) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
getBaseType() const GRT::MLBase
getClassType() const GRT::GRTBase
getGRTBasePointer()GRT::GRTBase
getGRTBasePointer() const GRT::GRTBase
getGRTRevison()GRT::GRTBasestatic
getGRTVersion(bool returnRevision=true)GRT::GRTBasestatic
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
getMaxNumEpochs() const GRT::MLBase
getMinChange() const GRT::MLBase
getMinNumEpochs() const GRT::MLBase
getMLBasePointer()GRT::MLBase
getMLBasePointer() const GRT::MLBase
getModel(ostream &stream) const GRT::MLBasevirtual
getModelAsString() const GRT::MLBasevirtual
getModelTrained() const GRT::MLBase
getNumInputDimensions() const GRT::MLBase
getNumInputFeatures() const GRT::MLBase
getNumOutputDimensions() const GRT::MLBase
getNumTrainingIterationsToConverge() const GRT::MLBase
getRandomiseTrainingOrder() const GRT::MLBase
getRootMeanSquaredTrainingError() const GRT::MLBase
getScalingEnabled() const GRT::MLBase
getTotalSquaredTrainingError() const GRT::MLBase
getTrained() const GRT::MLBase
getTrainingIterationLog() const (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
getTrainingResults() const GRT::MLBase
getUseValidationSet() const GRT::MLBase
getValidationSetSize() const GRT::MLBase
GRTBase(void)GRT::GRTBase
infoLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
learningRate (defined in GRT::MLBase)GRT::MLBaseprotected
load(const string filename)GRT::MLBasevirtual
loadBaseSettingsFromFile(fstream &file)GRT::MLBaseprotected
loadModelFromFile(fstream &file)GRT::DiscreteHiddenMarkovModelvirtual
GRT::MLBase::loadModelFromFile(string filename)GRT::MLBasevirtual
logLikelihood (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
map(VectorDouble inputVector)GRT::MLBasevirtual
map_(VectorDouble &inputVector)GRT::MLBasevirtual
maxNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
minChange (defined in GRT::MLBase)GRT::MLBaseprotected
minNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
MLBase(void)GRT::MLBase
modelType (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
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::MLBaseprotected
numOutputDimensions (defined in GRT::MLBase)GRT::MLBaseprotected
numRandomTrainingIterations (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
numStates (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
numSymbols (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
numTrainingIterationsToConverge (defined in GRT::MLBase)GRT::MLBaseprotected
observationSequence (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inline
Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inline
pi (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
predict(const UINT newSample) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
predict(const vector< UINT > &obs) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
GRT::MLBase::predict(VectorDouble inputVector)GRT::MLBasevirtual
GRT::MLBase::predict(MatrixDouble inputMatrix)GRT::MLBasevirtual
predict_(VectorDouble &inputVector)GRT::MLBasevirtual
predict_(MatrixDouble &inputMatrix)GRT::MLBasevirtual
predictLogLikelihood(const vector< UINT > &obs) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
print() const GRT::DiscreteHiddenMarkovModelvirtual
random (defined in GRT::MLBase)GRT::MLBaseprotected
randomiseTrainingOrder (defined in GRT::MLBase)GRT::MLBaseprotected
randomizeMatrices(const UINT numStates, const UINT numSymbols) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
registerTestResultsObserver(Observer< TestInstanceResult > &observer)GRT::MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)GRT::MLBase
REGRESSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
removeAllTestObservers()GRT::MLBase
removeAllTrainingObservers()GRT::MLBase
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)GRT::MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)GRT::MLBase
reset()GRT::DiscreteHiddenMarkovModelvirtual
resetModel(const UINT numStates, const UINT numSymbols, const UINT modelType, const UINT delta) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
rootMeanSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
save(const string filename) const GRT::MLBasevirtual
saveBaseSettingsToFile(fstream &file) const GRT::MLBaseprotected
saveModelToFile(fstream &file) const GRT::DiscreteHiddenMarkovModelvirtual
GRT::MLBase::saveModelToFile(string filename) const GRT::MLBasevirtual
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false)GRT::MLBaseinline
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::GRTBaseinlineprotected
testingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
testResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
totalSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
train(const vector< vector< UINT > > &trainingData) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
GRT::MLBase::train(ClassificationData trainingData)GRT::MLBasevirtual
GRT::MLBase::train(RegressionData trainingData)GRT::MLBasevirtual
GRT::MLBase::train(TimeSeriesClassificationData trainingData)GRT::MLBasevirtual
GRT::MLBase::train(TimeSeriesClassificationDataStream trainingData)GRT::MLBasevirtual
GRT::MLBase::train(UnlabelledData trainingData)GRT::MLBasevirtual
GRT::MLBase::train(MatrixDouble data)GRT::MLBasevirtual
train_(const vector< vector< UINT > > &obs, const UINT maxIter, UINT &currentIter, double &newLoglikelihood) (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
GRT::MLBase::train_(ClassificationData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(RegressionData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(TimeSeriesClassificationData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(TimeSeriesClassificationDataStream &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(UnlabelledData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(MatrixDouble &data)GRT::MLBasevirtual
trained (defined in GRT::MLBase)GRT::MLBaseprotected
trainingIterationLog (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModel
trainingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
trainingResults (defined in GRT::MLBase)GRT::MLBaseprotected
trainingResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
useScaling (defined in GRT::MLBase)GRT::MLBaseprotected
useValidationSet (defined in GRT::MLBase)GRT::MLBaseprotected
validationSetSize (defined in GRT::MLBase)GRT::MLBaseprotected
warningLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
~DiscreteHiddenMarkovModel() (defined in GRT::DiscreteHiddenMarkovModel)GRT::DiscreteHiddenMarkovModelvirtual
~GRTBase(void)GRT::GRTBasevirtual
~MLBase(void)GRT::MLBasevirtual
~Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inlinevirtual
~Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inlinevirtual