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::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::MLBase | virtual |
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::GRTBase | protected |
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::GRTBase | protected |
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::GRTBase | static |
getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
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::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 | |
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::GRTBase | protected |
learningRate (defined in GRT::MLBase) | GRT::MLBase | protected |
load(const string filename) | GRT::MLBase | virtual |
loadBaseSettingsFromFile(fstream &file) | GRT::MLBase | protected |
loadModelFromFile(fstream &file) | GRT::DiscreteHiddenMarkovModel | virtual |
GRT::MLBase::loadModelFromFile(string filename) | GRT::MLBase | virtual |
logLikelihood (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | |
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 | |
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::MLBase | protected |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
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::MLBase | protected |
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::MLBase | virtual |
GRT::MLBase::predict(MatrixDouble inputMatrix) | GRT::MLBase | virtual |
predict_(VectorDouble &inputVector) | GRT::MLBase | virtual |
predict_(MatrixDouble &inputMatrix) | GRT::MLBase | virtual |
predictLogLikelihood(const vector< UINT > &obs) (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | |
print() const | GRT::DiscreteHiddenMarkovModel | virtual |
random (defined in GRT::MLBase) | GRT::MLBase | protected |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | protected |
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::DiscreteHiddenMarkovModel | virtual |
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::MLBase | protected |
save(const string filename) const | GRT::MLBase | virtual |
saveBaseSettingsToFile(fstream &file) const | GRT::MLBase | protected |
saveModelToFile(fstream &file) const | GRT::DiscreteHiddenMarkovModel | virtual |
GRT::MLBase::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 | |
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 |
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(const vector< vector< UINT > > &trainingData) (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | |
GRT::MLBase::train(ClassificationData trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train(RegressionData trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train(TimeSeriesClassificationData trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train(TimeSeriesClassificationDataStream trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train(UnlabelledData trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train(MatrixDouble data) | GRT::MLBase | virtual |
train_(const vector< vector< UINT > > &obs, const UINT maxIter, UINT ¤tIter, double &newLoglikelihood) (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | |
GRT::MLBase::train_(ClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(RegressionData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(TimeSeriesClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(TimeSeriesClassificationDataStream &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(UnlabelledData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(MatrixDouble &data) | GRT::MLBase | virtual |
trained (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingIterationLog (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | |
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 |
~DiscreteHiddenMarkovModel() (defined in GRT::DiscreteHiddenMarkovModel) | GRT::DiscreteHiddenMarkovModel | virtual |
~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 |