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.
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This is the complete list of members for ContinuousHiddenMarkovModel, including all inherited members.
a | ContinuousHiddenMarkovModel | protected |
alpha (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
autoEstimateSigma (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
b | ContinuousHiddenMarkovModel | protected |
BASE_TYPE_NOT_SET enum value (defined in MLBase) | MLBase | |
BaseType enum name (defined in MLBase) | MLBase | |
baseType (defined in MLBase) | MLBase | protected |
batchSize (defined in MLBase) | MLBase | protected |
c (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
classId | GRTBase | protected |
CLASSIFIER enum value (defined in MLBase) | MLBase | |
classLabel | ContinuousHiddenMarkovModel | protected |
clear() override | ContinuousHiddenMarkovModel | virtual |
CLUSTERER enum value (defined in MLBase) | MLBase | |
CONTEXT enum value (defined in MLBase) | MLBase | |
ContinuousHiddenMarkovModel(const UINT downsampleFactor=5, const UINT delta=1, const bool autoEstimateSigma=true, const Float sigma=10.0) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
ContinuousHiddenMarkovModel(const ContinuousHiddenMarkovModel &rhs) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
converged (defined in MLBase) | MLBase | protected |
copyGRTBaseVariables(const GRTBase *GRTBase) | GRTBase | |
copyMLBaseVariables(const MLBase *mlBase) | MLBase | |
cThreshold | ContinuousHiddenMarkovModel | protected |
debugLog (defined in GRTBase) | GRTBase | protected |
delta | ContinuousHiddenMarkovModel | protected |
downsampleFactor (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
enableScaling(const bool useScaling) | MLBase | |
errorLog (defined in GRTBase) | GRTBase | protected |
estimatedStates | ContinuousHiddenMarkovModel | protected |
FEATURE_EXTRACTION enum value (defined in MLBase) | MLBase | |
gauss(const MatrixFloat &x, const MatrixFloat &y, const MatrixFloat &sigma, const unsigned int i, const unsigned int j, const unsigned int N) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
getAlpha() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getBatchSize() const | MLBase | |
getClassLabel() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getConverged() const | MLBase | |
getEstimatedStates() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getGRTBasePointer() | GRTBase | |
getGRTBasePointer() const | GRTBase | |
getGRTRevison() | GRTBase | static |
getGRTVersion(bool returnRevision=true) | GRTBase | static |
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 | |
getLoglikelihood() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getMaxNumEpochs() const | MLBase | |
getMinChange() const | MLBase | |
getMinNumEpochs() const | MLBase | |
getMLBasePointer() | MLBase | |
getMLBasePointer() const | MLBase | |
getModel(std::ostream &stream) const | MLBase | virtual |
getModelAsString() const | MLBase | virtual |
getNumInputDimensions() const | MLBase | |
getNumInputFeatures() const | MLBase | |
getNumOutputDimensions() const | MLBase | |
getNumRestarts() const | MLBase | |
getNumStates() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getNumTrainingIterationsToConverge() const | MLBase | |
getOutputType() const | MLBase | |
getPhase() const (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | inline |
getRandomiseTrainingOrder() const | MLBase | |
getRMSTrainingError() const | MLBase | |
getRMSValidationError() const | MLBase | |
getScalingEnabled() const | MLBase | |
getTestingLoggingEnabled() const | MLBase | |
getTotalSquaredTrainingError() const | MLBase | |
getTrained() const | MLBase | |
getTrainingLoggingEnabled() const | MLBase | |
getTrainingResults() const | MLBase | |
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) | GRTBase | protected |
inputType (defined in MLBase) | MLBase | protected |
learningRate (defined in MLBase) | MLBase | protected |
load(std::fstream &file) override | ContinuousHiddenMarkovModel | virtual |
MLBase::load(const std::string &filename) | MLBase | virtual |
loadBaseSettingsFromFile(std::fstream &file) | MLBase | protected |
loglikelihood | ContinuousHiddenMarkovModel | protected |
map(VectorFloat inputVector) | MLBase | virtual |
map_(VectorFloat &inputVector) | MLBase | virtual |
maxNumEpochs (defined in MLBase) | MLBase | protected |
minChange (defined in MLBase) | MLBase | protected |
minNumEpochs (defined in MLBase) | MLBase | protected |
MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET) | MLBase | |
modelType | ContinuousHiddenMarkovModel | protected |
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) | MLBase | protected |
numOutputDimensions (defined in MLBase) | MLBase | protected |
numRestarts (defined in MLBase) | MLBase | protected |
numStates | ContinuousHiddenMarkovModel | protected |
numTrainingIterationsToConverge (defined in MLBase) | MLBase | protected |
observationSequence | ContinuousHiddenMarkovModel | protected |
Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inline |
Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inline |
obsSequence (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
operator=(const ContinuousHiddenMarkovModel &rhs) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
outputType (defined in MLBase) | MLBase | protected |
phase (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
pi | ContinuousHiddenMarkovModel | protected |
POST_PROCESSING enum value (defined in MLBase) | MLBase | |
PRE_PROCSSING enum value (defined in MLBase) | MLBase | |
predict(VectorFloat inputVector) | MLBase | virtual |
predict(MatrixFloat inputMatrix) | MLBase | virtual |
predict_(VectorFloat &x) override | ContinuousHiddenMarkovModel | virtual |
predict_(MatrixFloat &obs) override | ContinuousHiddenMarkovModel | virtual |
print() const override | ContinuousHiddenMarkovModel | virtual |
random (defined in MLBase) | MLBase | protected |
randomiseTrainingOrder (defined in MLBase) | MLBase | protected |
registerTestResultsObserver(Observer< TestInstanceResult > &observer) | MLBase | |
registerTrainingResultsObserver(Observer< TrainingResult > &observer) | MLBase | |
REGRESSIFIER enum value (defined in MLBase) | MLBase | |
removeAllTestObservers() | MLBase | |
removeAllTrainingObservers() | MLBase | |
removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | MLBase | |
removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | MLBase | |
reset() override | ContinuousHiddenMarkovModel | virtual |
rmsTrainingError (defined in MLBase) | MLBase | protected |
rmsValidationError (defined in MLBase) | MLBase | protected |
save(std::fstream &file) const override | ContinuousHiddenMarkovModel | virtual |
MLBase::save(const std::string &filename) const | MLBase | virtual |
saveBaseSettingsToFile(std::fstream &file) const | MLBase | protected |
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false) | GRTBase | inline |
setAutoEstimateSigma(const bool autoEstimateSigma) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
setBatchSize(const UINT batchSize) | MLBase | |
setDebugLoggingEnabled(const bool loggingEnabled) | GRTBase | |
setDelta(const UINT delta) | ContinuousHiddenMarkovModel | |
setDownsampleFactor(const UINT downsampleFactor) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
setErrorLoggingEnabled(const bool loggingEnabled) | GRTBase | |
setInfoLoggingEnabled(const bool loggingEnabled) | GRTBase | |
setLearningRate(const Float learningRate) | MLBase | |
setMaxNumEpochs(const UINT maxNumEpochs) | MLBase | |
setMinChange(const Float minChange) | MLBase | |
setMinNumEpochs(const UINT minNumEpochs) | MLBase | |
setModelType(const UINT modelType) | ContinuousHiddenMarkovModel | |
setNumRestarts(const UINT numRestarts) | MLBase | |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | MLBase | |
setSigma(const Float sigma) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | |
setTestingLoggingEnabled(const bool loggingEnabled) | MLBase | |
setTrainingLoggingEnabled(const bool loggingEnabled) | MLBase | |
setUseValidationSet(const bool useValidationSet) | MLBase | |
setValidationSetSize(const UINT validationSetSize) | MLBase | |
setWarningLoggingEnabled(const bool loggingEnabled) | GRTBase | |
sigma (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | protected |
sigmaStates | ContinuousHiddenMarkovModel | protected |
SQR(const Float &x) const (defined in GRTBase) | GRTBase | inline |
testingLog (defined in MLBase) | MLBase | protected |
testResultsObserverManager (defined in MLBase) | MLBase | protected |
timeseriesLength | ContinuousHiddenMarkovModel | protected |
totalSquaredTrainingError (defined in MLBase) | MLBase | protected |
train(ClassificationData trainingData) | MLBase | virtual |
train(RegressionData trainingData) | MLBase | virtual |
train(RegressionData trainingData, RegressionData validationData) | MLBase | virtual |
train(TimeSeriesClassificationData trainingData) | MLBase | virtual |
train(ClassificationDataStream trainingData) | MLBase | virtual |
train(UnlabelledData trainingData) | MLBase | virtual |
train(MatrixFloat data) | MLBase | virtual |
train_(TimeSeriesClassificationSample &trainingData) (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | virtual |
MLBase::train_(ClassificationData &trainingData) | MLBase | virtual |
MLBase::train_(RegressionData &trainingData) | MLBase | virtual |
MLBase::train_(RegressionData &trainingData, RegressionData &validationData) | MLBase | virtual |
MLBase::train_(TimeSeriesClassificationData &trainingData) | MLBase | virtual |
MLBase::train_(ClassificationDataStream &trainingData) | MLBase | virtual |
MLBase::train_(UnlabelledData &trainingData) | MLBase | virtual |
MLBase::train_(MatrixFloat &data) | MLBase | virtual |
trained (defined in MLBase) | MLBase | protected |
trainingLog (defined in MLBase) | MLBase | protected |
trainingResults (defined in MLBase) | MLBase | protected |
trainingResultsObserverManager (defined in MLBase) | MLBase | protected |
useScaling (defined in MLBase) | MLBase | protected |
useValidationSet (defined in MLBase) | MLBase | protected |
validationSetAccuracy (defined in MLBase) | MLBase | protected |
validationSetPrecision (defined in MLBase) | MLBase | protected |
validationSetRecall (defined in MLBase) | MLBase | protected |
validationSetSize (defined in MLBase) | MLBase | protected |
warningLog (defined in GRTBase) | GRTBase | protected |
~ContinuousHiddenMarkovModel() (defined in ContinuousHiddenMarkovModel) | ContinuousHiddenMarkovModel | virtual |
~GRTBase(void) | GRTBase | virtual |
~MLBase(void) | MLBase | virtual |
~Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlinevirtual |
~Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlinevirtual |