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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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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 RegisterFeatureExtractionModule< T >, including all inherited members.
| BASE_TYPE_NOT_SET enum value (defined in MLBase) | MLBase | private |
| baseType (defined in MLBase) | MLBase | private |
| BaseType enum name (defined in MLBase) | MLBase | private |
| batchSize (defined in MLBase) | MLBase | private |
| classId | GRTBase | private |
| CLASSIFIER enum value (defined in MLBase) | MLBase | private |
| clear() override | FeatureExtraction | privatevirtual |
| CLUSTERER enum value (defined in MLBase) | MLBase | private |
| computeFeatures(const VectorFloat &inputVector) | FeatureExtraction | inlineprivatevirtual |
| computeFeatures(const MatrixFloat &inputMatrix) | FeatureExtraction | inlineprivatevirtual |
| CONTEXT enum value (defined in MLBase) | MLBase | private |
| converged (defined in MLBase) | MLBase | private |
| copyBaseVariables(const FeatureExtraction *featureExtractionModule) | FeatureExtraction | private |
| copyGRTBaseVariables(const GRTBase *GRTBase) | GRTBase | private |
| copyMLBaseVariables(const MLBase *mlBase) | MLBase | private |
| create(const std::string &id) (defined in FeatureExtraction) | FeatureExtraction | privatestatic |
| create() const | FeatureExtraction | private |
| debugLog (defined in GRTBase) | GRTBase | private |
| deepCopyFrom(const FeatureExtraction *rhs) | FeatureExtraction | inlineprivatevirtual |
| enableScaling(const bool useScaling) | MLBase | private |
| errorLog (defined in GRTBase) | GRTBase | private |
| FEATURE_EXTRACTION enum value (defined in MLBase) | MLBase | private |
| featureDataReady (defined in FeatureExtraction) | FeatureExtraction | private |
| FeatureExtraction(const std::string id="") | FeatureExtraction | private |
| featureExtractionType (defined in FeatureExtraction) | FeatureExtraction | private |
| featureMatrix (defined in FeatureExtraction) | FeatureExtraction | private |
| featureVector (defined in FeatureExtraction) | FeatureExtraction | private |
| getBatchSize() const | MLBase | private |
| getConverged() const | MLBase | private |
| getFeatureDataReady() const | FeatureExtraction | private |
| getFeatureMatrix() const | FeatureExtraction | private |
| getFeatureVector() const | FeatureExtraction | private |
| getGRTBasePointer() | GRTBase | private |
| getGRTBasePointer() const | GRTBase | private |
| getGRTRevison() | GRTBase | privatestatic |
| getGRTVersion(bool returnRevision=true) | GRTBase | privatestatic |
| getId() const | GRTBase | private |
| getInitialized() const | FeatureExtraction | private |
| getInputType() const | MLBase | private |
| getIsBaseTypeClassifier() const | MLBase | private |
| getIsBaseTypeClusterer() const | MLBase | private |
| getIsBaseTypeRegressifier() const | MLBase | private |
| getLastErrorMessage() const | GRTBase | private |
| getLastInfoMessage() const | GRTBase | private |
| getLastWarningMessage() const | GRTBase | private |
| getLearningRate() const | MLBase | private |
| getMap() (defined in FeatureExtraction) | FeatureExtraction | inlineprivatestatic |
| getMaxNumEpochs() const | MLBase | private |
| getMinChange() const | MLBase | private |
| getMinNumEpochs() const | MLBase | private |
| getMLBasePointer() | MLBase | private |
| getMLBasePointer() const | MLBase | private |
| getModel(std::ostream &stream) const | MLBase | privatevirtual |
| getModelAsString() const | MLBase | privatevirtual |
| getNumInputDimensions() const | MLBase | private |
| getNumInputFeatures() const | MLBase | private |
| getNumOutputDimensions() const | MLBase | private |
| getNumRestarts() const | MLBase | private |
| getNumTrainingIterationsToConverge() const | MLBase | private |
| getOutputType() const | MLBase | private |
| getRandomiseTrainingOrder() const | MLBase | private |
| getRMSTrainingError() const | MLBase | private |
| getRMSValidationError() const | MLBase | private |
| getScalingEnabled() const | MLBase | private |
| getTestingLoggingEnabled() const | MLBase | private |
| getTotalSquaredTrainingError() const | MLBase | private |
| getTrained() const | MLBase | private |
| getTrainingLoggingEnabled() const | MLBase | private |
| getTrainingResults() const | MLBase | private |
| getType() const | MLBase | private |
| getUseValidationSet() const | MLBase | private |
| getValidationSetAccuracy() const | MLBase | private |
| getValidationSetPrecision() const | MLBase | private |
| getValidationSetRecall() const | MLBase | private |
| getValidationSetSize() const | MLBase | private |
| GRT_DEPRECATED_MSG("createNewInstance is deprecated, use create() instead.", FeatureExtraction *createNewInstance() const ) (defined in FeatureExtraction) | FeatureExtraction | private |
| GRT_DEPRECATED_MSG("createInstanceFromString(id) is deprecated, use create(id) instead.", static FeatureExtraction *createInstanceFromString(const std::string &id)) (defined in FeatureExtraction) | FeatureExtraction | private |
| GRT_DEPRECATED_MSG("getFeatureExtractionType is deprecated, use getId() instead", std::string getFeatureExtractionType() const ) (defined in FeatureExtraction) | FeatureExtraction | private |
| 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 | private |
| MLBase::GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const ) | MLBase | private |
| 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 | private |
| MLBase::GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file)) | MLBase | private |
| MLBase::GRT_DEPRECATED_MSG("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const ) | MLBase | private |
| MLBase::GRT_DEPRECATED_MSG("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const ) | MLBase | private |
| GRTBase::GRT_DEPRECATED_MSG("getClassType is deprecated, use getId() instead!", std::string getClassType() const ) | GRTBase | private |
| GRTBase(const std::string &id="") | GRTBase | private |
| infoLog (defined in GRTBase) | GRTBase | private |
| init() | FeatureExtraction | private |
| initialized (defined in FeatureExtraction) | FeatureExtraction | private |
| inputType (defined in MLBase) | MLBase | private |
| learningRate (defined in MLBase) | MLBase | private |
| load(const std::string &filename) | MLBase | privatevirtual |
| load(std::fstream &file) | MLBase | privatevirtual |
| loadBaseSettingsFromFile(std::fstream &file) | MLBase | private |
| loadFeatureExtractionSettingsFromFile(std::fstream &file) | FeatureExtraction | private |
| map(VectorFloat inputVector) | MLBase | privatevirtual |
| map_(VectorFloat &inputVector) | MLBase | privatevirtual |
| maxNumEpochs (defined in MLBase) | MLBase | private |
| minChange (defined in MLBase) | MLBase | private |
| minNumEpochs (defined in MLBase) | MLBase | private |
| MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET) | MLBase | private |
| notify(const TrainingResult &data) (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlineprivatevirtual |
| notify(const TestInstanceResult &data) (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlineprivatevirtual |
| notifyTestResultsObservers(const TestInstanceResult &data) | MLBase | private |
| notifyTrainingResultsObservers(const TrainingResult &data) | MLBase | private |
| numInputDimensions (defined in MLBase) | MLBase | private |
| numOutputDimensions (defined in MLBase) | MLBase | private |
| numRestarts (defined in MLBase) | MLBase | private |
| numTrainingIterationsToConverge (defined in MLBase) | MLBase | private |
| Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlineprivate |
| Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlineprivate |
| outputType (defined in MLBase) | MLBase | private |
| POST_PROCESSING enum value (defined in MLBase) | MLBase | private |
| PRE_PROCSSING enum value (defined in MLBase) | MLBase | private |
| predict(VectorFloat inputVector) | MLBase | privatevirtual |
| predict(MatrixFloat inputMatrix) | MLBase | privatevirtual |
| predict_(VectorFloat &inputVector) | MLBase | privatevirtual |
| predict_(MatrixFloat &inputMatrix) | MLBase | privatevirtual |
| print() const | MLBase | privatevirtual |
| random (defined in MLBase) | MLBase | private |
| randomiseTrainingOrder (defined in MLBase) | MLBase | private |
| RegisterFeatureExtractionModule(const std::string &newModuleId) (defined in RegisterFeatureExtractionModule< T >) | RegisterFeatureExtractionModule< T > | inline |
| registerTestResultsObserver(Observer< TestInstanceResult > &observer) | MLBase | private |
| registerTrainingResultsObserver(Observer< TrainingResult > &observer) | MLBase | private |
| REGRESSIFIER enum value (defined in MLBase) | MLBase | private |
| removeAllTestObservers() | MLBase | private |
| removeAllTrainingObservers() | MLBase | private |
| removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | MLBase | private |
| removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | MLBase | private |
| reset() | MLBase | privatevirtual |
| rmsTrainingError (defined in MLBase) | MLBase | private |
| rmsValidationError (defined in MLBase) | MLBase | private |
| save(const std::string &filename) const | MLBase | privatevirtual |
| save(std::fstream &file) const | MLBase | privatevirtual |
| saveBaseSettingsToFile(std::fstream &file) const | MLBase | private |
| saveFeatureExtractionSettingsToFile(std::fstream &file) const | FeatureExtraction | private |
| scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false) | GRTBase | inlineprivate |
| setBatchSize(const UINT batchSize) | MLBase | private |
| setDebugLoggingEnabled(const bool loggingEnabled) | GRTBase | private |
| setErrorLoggingEnabled(const bool loggingEnabled) | GRTBase | private |
| setInfoLoggingEnabled(const bool loggingEnabled) | GRTBase | private |
| setLearningRate(const Float learningRate) | MLBase | private |
| setMaxNumEpochs(const UINT maxNumEpochs) | MLBase | private |
| setMinChange(const Float minChange) | MLBase | private |
| setMinNumEpochs(const UINT minNumEpochs) | MLBase | private |
| setNumRestarts(const UINT numRestarts) | MLBase | private |
| setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | MLBase | private |
| setTestingLoggingEnabled(const bool loggingEnabled) | MLBase | private |
| setTrainingLoggingEnabled(const bool loggingEnabled) | MLBase | private |
| setUseValidationSet(const bool useValidationSet) | MLBase | private |
| setValidationSetSize(const UINT validationSetSize) | MLBase | private |
| setWarningLoggingEnabled(const bool loggingEnabled) | GRTBase | private |
| SQR(const Float &x) const (defined in GRTBase) | GRTBase | inlineprivate |
| StringFeatureExtractionMap typedef | FeatureExtraction | private |
| testingLog (defined in MLBase) | MLBase | private |
| testResultsObserverManager (defined in MLBase) | MLBase | private |
| totalSquaredTrainingError (defined in MLBase) | MLBase | private |
| train(ClassificationData trainingData) | MLBase | privatevirtual |
| train(RegressionData trainingData) | MLBase | privatevirtual |
| train(RegressionData trainingData, RegressionData validationData) | MLBase | privatevirtual |
| train(TimeSeriesClassificationData trainingData) | MLBase | privatevirtual |
| train(ClassificationDataStream trainingData) | MLBase | privatevirtual |
| train(UnlabelledData trainingData) | MLBase | privatevirtual |
| train(MatrixFloat data) | MLBase | privatevirtual |
| train_(ClassificationData &trainingData) | MLBase | privatevirtual |
| train_(RegressionData &trainingData) | MLBase | privatevirtual |
| train_(RegressionData &trainingData, RegressionData &validationData) | MLBase | privatevirtual |
| train_(TimeSeriesClassificationData &trainingData) | MLBase | privatevirtual |
| train_(ClassificationDataStream &trainingData) | MLBase | privatevirtual |
| train_(UnlabelledData &trainingData) | MLBase | privatevirtual |
| train_(MatrixFloat &data) | MLBase | privatevirtual |
| trained (defined in MLBase) | MLBase | private |
| trainingLog (defined in MLBase) | MLBase | private |
| trainingResults (defined in MLBase) | MLBase | private |
| trainingResultsObserverManager (defined in MLBase) | MLBase | private |
| useScaling (defined in MLBase) | MLBase | private |
| useValidationSet (defined in MLBase) | MLBase | private |
| validationSetAccuracy (defined in MLBase) | MLBase | private |
| validationSetPrecision (defined in MLBase) | MLBase | private |
| validationSetRecall (defined in MLBase) | MLBase | private |
| validationSetSize (defined in MLBase) | MLBase | private |
| warningLog (defined in GRTBase) | GRTBase | private |
| ~FeatureExtraction() | FeatureExtraction | privatevirtual |
| ~GRTBase(void) | GRTBase | privatevirtual |
| ~MLBase(void) | MLBase | privatevirtual |
| ~Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlineprivatevirtual |
| ~Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlineprivatevirtual |
1.8.11 
