 |
GestureRecognitionToolkit
Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
|
|
GestureRecognitionToolkit
Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
|
This is the complete list of members for SVM, including all inherited members.
| BASE_TYPE_NOT_SET enum value (defined in MLBase) | MLBase | |
| baseType (defined in MLBase) | MLBase | protected |
| BaseTypes enum name (defined in MLBase) | MLBase | |
| bestDistance (defined in Classifier) | Classifier | protected |
| C_SVC enum value (defined in SVM) | SVM | |
| classDistances (defined in Classifier) | Classifier | protected |
| classificationThreshold (defined in SVM) | SVM | protected |
| CLASSIFIER enum value (defined in MLBase) | MLBase | |
| Classifier(void) | Classifier | |
| classifierMode (defined in Classifier) | Classifier | protected |
| ClassifierModes enum name (defined in Classifier) | Classifier | |
| classifierType (defined in Classifier) | Classifier | protected |
| classLabels (defined in Classifier) | Classifier | protected |
| classLikelihoods (defined in Classifier) | Classifier | protected |
| classType (defined in GRTBase) | GRTBase | protected |
| clear() | SVM | virtual |
| CLUSTERER enum value (defined in MLBase) | MLBase | |
| convertClassificationDataToLIBSVMFormat(ClassificationData &trainingData) (defined in SVM) | SVM | protected |
| copyBaseVariables(const Classifier *classifier) | Classifier | |
| copyGRTBaseVariables(const GRTBase *GRTBase) | GRTBase | |
| copyMLBaseVariables(const MLBase *mlBase) | MLBase | |
| createInstanceFromString(std::string const &classifierType) | Classifier | static |
| createNewInstance() const | Classifier | |
| crossValidationResult (defined in SVM) | SVM | protected |
| debugLog (defined in GRTBase) | GRTBase | protected |
| deepCopy() const | Classifier | |
| deepCopyFrom(const Classifier *classifier) | SVM | virtual |
| deepCopyModel() const (defined in SVM) | SVM | protected |
| deepCopyParam(const svm_parameter &source_param, svm_parameter &target_param) const (defined in SVM) | SVM | protected |
| deepCopyProblem(const struct svm_problem &source_problem, struct svm_problem &target_problem, const unsigned int numInputDimensions) const (defined in SVM) | SVM | protected |
| deleteProblemSet() (defined in SVM) | SVM | protected |
| enableAutoGamma(const bool useAutoGamma) | SVM | |
| enableCrossValidationTraining(const bool useCrossValidation) | SVM | |
| enableNullRejection(bool useNullRejection) | Classifier | |
| enableScaling(const bool useScaling) | MLBase | |
| EPSILON_SVR enum value (defined in SVM) | SVM | |
| errorLog (defined in GRTBase) | GRTBase | protected |
| getBaseClassifier() const | Classifier | |
| getBaseType() const | MLBase | |
| getBestDistance() const | Classifier | |
| getC() const | SVM | |
| getClassDistances() const | Classifier | |
| getClassifierPointer() const | Classifier | |
| getClassifierType() const | Classifier | |
| getClassLabelIndexValue(UINT classLabel) const | Classifier | |
| getClassLabels() const | Classifier | |
| getClassLikelihoods() const | Classifier | |
| getClassType() const | GRTBase | |
| getCoef0() const | SVM | |
| getCrossValidationResult() const | SVM | |
| getDegree() const | SVM | |
| getGamma() const | SVM | |
| getGRTBasePointer() | GRTBase | |
| getGRTBasePointer() const | GRTBase | |
| getGRTRevison() | GRTBase | static |
| getGRTVersion(bool returnRevision=true) | GRTBase | static |
| getInputType() const | MLBase | |
| getIsAutoGammaEnabled() const | SVM | |
| getIsBaseTypeClassifier() const | MLBase | |
| getIsBaseTypeClusterer() const | MLBase | |
| getIsBaseTypeRegressifier() const | MLBase | |
| getIsCrossValidationTrainingEnabled() const | SVM | |
| getKernelType() const | SVM | |
| getLastErrorMessage() const | GRTBase | |
| getLastInfoMessage() const | GRTBase | |
| getLastWarningMessage() const | GRTBase | |
| getLearningRate() const | MLBase | |
| getMap() | Classifier | inlineprotectedstatic |
| getMaximumLikelihood() const | Classifier | |
| getMaxNumEpochs() const | MLBase | |
| getMinChange() const | MLBase | |
| getMinNumEpochs() const | MLBase | |
| getMLBasePointer() | MLBase | |
| getMLBasePointer() const | MLBase | |
| getModel() const (defined in SVM) | SVM | inline |
| Classifier::getModel(std::ostream &stream) const | MLBase | virtual |
| getModelAsString() const | MLBase | virtual |
| getModelTrained() const | MLBase | |
| getNu() const | SVM | |
| getNullRejectionCoeff() const | Classifier | |
| getNullRejectionEnabled() const | Classifier | |
| getNullRejectionThresholds() const | Classifier | |
| getNumClasses() const | SVM | virtual |
| getNumInputDimensions() const | MLBase | |
| getNumInputFeatures() const | MLBase | |
| getNumOutputDimensions() const | MLBase | |
| getNumTrainingIterationsToConverge() const | MLBase | |
| getOutputType() const | MLBase | |
| getPhase() const | Classifier | |
| getPredictedClassLabel() const | Classifier | |
| getRandomiseTrainingOrder() const | MLBase | |
| getRanges() const | Classifier | |
| getRegisteredClassifiers() | Classifier | static |
| getRootMeanSquaredTrainingError() const | MLBase | |
| getScalingEnabled() const | MLBase | |
| getSupportsNullRejection() const | Classifier | |
| getSVMType() const | SVM | |
| getTimeseriesCompatible() const | Classifier | inline |
| getTotalSquaredTrainingError() const | MLBase | |
| getTrained() const | MLBase | |
| getTrainingResults() 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(std::string filename) instead", virtual bool saveModelToFile(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(std::string filename) instead", virtual bool loadModelFromFile(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 | |
| GRTBase(void) | GRTBase | |
| infoLog (defined in GRTBase) | GRTBase | protected |
| init(UINT kernelType, UINT svmType, bool useScaling, bool useNullRejection, bool useAutoGamma, Float gamma, UINT degree, Float coef0, Float nu, Float C, bool useCrossValidation, UINT kFoldValue) | SVM | |
| initDefaultSVMSettings() | SVM | |
| inputType (defined in MLBase) | MLBase | protected |
| kFoldValue (defined in SVM) | SVM | protected |
| learningRate (defined in MLBase) | MLBase | protected |
| LINEAR_KERNEL enum value (defined in SVM) | SVM | |
| load(std::fstream &file) | SVM | virtual |
| Classifier::load(const std::string filename) | MLBase | virtual |
| loadBaseSettingsFromFile(std::fstream &file) | Classifier | protected |
| loadLegacyModelFromFile(std::fstream &file) | SVM | protected |
| map(VectorFloat inputVector) | MLBase | virtual |
| map_(VectorFloat &inputVector) | MLBase | virtual |
| maxLikelihood (defined in Classifier) | Classifier | protected |
| maxNumEpochs (defined in MLBase) | MLBase | protected |
| minChange (defined in MLBase) | MLBase | protected |
| minNumEpochs (defined in MLBase) | MLBase | protected |
| MLBase(void) | MLBase | |
| model (defined in SVM) | SVM | 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 | |
| NU_SVC enum value (defined in SVM) | SVM | |
| NU_SVR enum value (defined in SVM) | SVM | |
| nullRejectionCoeff (defined in Classifier) | Classifier | protected |
| nullRejectionThresholds (defined in Classifier) | Classifier | protected |
| numClasses (defined in Classifier) | Classifier | protected |
| numInputDimensions (defined in MLBase) | MLBase | protected |
| numOutputDimensions (defined in MLBase) | MLBase | protected |
| numTrainingIterationsToConverge (defined in MLBase) | MLBase | protected |
| Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inline |
| Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inline |
| ONE_CLASS enum value (defined in SVM) | SVM | |
| operator=(const SVM &rhs) | SVM | |
| outputType (defined in MLBase) | MLBase | protected |
| param (defined in SVM) | SVM | protected |
| phase (defined in Classifier) | Classifier | protected |
| POLY_KERNEL enum value (defined in SVM) | SVM | |
| PRECOMPUTED_KERNEL enum value (defined in SVM) | SVM | |
| predict(VectorFloat inputVector) | MLBase | virtual |
| predict(MatrixFloat inputMatrix) | MLBase | virtual |
| predict_(VectorFloat &inputVector) | SVM | virtual |
| Classifier::predict_(MatrixFloat &inputMatrix) | MLBase | virtual |
| predictedClassLabel (defined in Classifier) | Classifier | protected |
| predictSVM(VectorFloat &inputVector) (defined in SVM) | SVM | protected |
| predictSVM(VectorFloat &inputVector, Float &maxProbability, VectorFloat &probabilites) (defined in SVM) | SVM | protected |
| print() const | MLBase | virtual |
| prob (defined in SVM) | SVM | protected |
| problemSet (defined in SVM) | SVM | protected |
| random (defined in MLBase) | MLBase | protected |
| randomiseTrainingOrder (defined in MLBase) | MLBase | protected |
| ranges (defined in Classifier) | Classifier | protected |
| RBF_KERNEL enum value (defined in SVM) | SVM | |
| recomputeNullRejectionThresholds() | Classifier | inlinevirtual |
| registerModule (defined in SVM) | SVM | protectedstatic |
| 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() | Classifier | virtual |
| rootMeanSquaredTrainingError (defined in MLBase) | MLBase | protected |
| save(std::fstream &file) const | SVM | virtual |
| Classifier::save(const std::string filename) const | MLBase | virtual |
| saveBaseSettingsToFile(std::fstream &file) const | Classifier | protected |
| scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false) | MLBase | inline |
| setC(const Float C) | SVM | |
| setCoef0(const Float coef0) | SVM | |
| setDegree(const UINT degree) | SVM | |
| setErrorLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setGamma(const Float gamma) | SVM | |
| setInfoLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setKernelType(const UINT kernelType) | SVM | |
| setKFoldCrossValidationValue(const UINT kFoldValue) | SVM | |
| setLearningRate(const Float learningRate) | MLBase | |
| setMaxNumEpochs(const UINT maxNumEpochs) | MLBase | |
| setMinChange(const Float minChange) | MLBase | |
| setMinNumEpochs(const UINT minNumEpochs) | MLBase | |
| setNu(const Float nu) | SVM | |
| setNullRejectionCoeff(Float nullRejectionCoeff) | Classifier | virtual |
| setNullRejectionThresholds(VectorFloat newRejectionThresholds) | Classifier | virtual |
| setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | MLBase | |
| setSVMType(const UINT svmType) | SVM | |
| setTrainingLoggingEnabled(const bool loggingEnabled) | MLBase | |
| setUseValidationSet(const bool useValidationSet) | MLBase | |
| setValidationSetSize(const UINT validationSetSize) | MLBase | |
| setWarningLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| SIGMOID_KERNEL enum value (defined in SVM) | SVM | |
| SQR(const Float &x) const (defined in GRTBase) | GRTBase | inlineprotected |
| STANDARD_CLASSIFIER_MODE enum value (defined in Classifier) | Classifier | |
| StringClassifierMap typedef | Classifier | |
| supportsNullRejection (defined in Classifier) | Classifier | protected |
| SVM(UINT kernelType=LINEAR_KERNEL, UINT svmType=C_SVC, bool useScaling=true, bool useNullRejection=false, bool useAutoGamma=true, Float gamma=0.1, UINT degree=3, Float coef0=0, Float nu=0.5, Float C=1, bool useCrossValidation=false, UINT kFoldValue=10) | SVM | |
| SVM(const SVM &rhs) | SVM | |
| SVMKernelTypes enum name (defined in SVM) | SVM | |
| SVMTypes enum name (defined in SVM) | SVM | |
| testingLog (defined in GRTBase) | GRTBase | protected |
| testResultsObserverManager (defined in MLBase) | MLBase | protected |
| TIMESERIES_CLASSIFIER_MODE enum value (defined in Classifier) | Classifier | |
| totalSquaredTrainingError (defined in MLBase) | MLBase | protected |
| train(ClassificationData trainingData) | MLBase | virtual |
| train(RegressionData trainingData) | MLBase | virtual |
| train(TimeSeriesClassificationData trainingData) | MLBase | virtual |
| train(ClassificationDataStream trainingData) | MLBase | virtual |
| train(UnlabelledData trainingData) | MLBase | virtual |
| train(MatrixFloat data) | MLBase | virtual |
| train_(ClassificationData &trainingData) | SVM | virtual |
| Classifier::train_(RegressionData &trainingData) | MLBase | virtual |
| Classifier::train_(TimeSeriesClassificationData &trainingData) | MLBase | virtual |
| Classifier::train_(ClassificationDataStream &trainingData) | MLBase | virtual |
| Classifier::train_(UnlabelledData &trainingData) | MLBase | virtual |
| Classifier::train_(MatrixFloat &data) | MLBase | virtual |
| trained (defined in MLBase) | MLBase | protected |
| trainingLog (defined in GRTBase) | GRTBase | protected |
| trainingResults (defined in MLBase) | MLBase | protected |
| trainingResultsObserverManager (defined in MLBase) | MLBase | protected |
| trainSVM() (defined in SVM) | SVM | protected |
| useAutoGamma (defined in SVM) | SVM | protected |
| useCrossValidation (defined in SVM) | SVM | protected |
| useNullRejection (defined in Classifier) | Classifier | protected |
| useScaling (defined in MLBase) | MLBase | protected |
| useValidationSet (defined in MLBase) | MLBase | protected |
| validateKernelType(UINT kernelType) (defined in SVM) | SVM | protected |
| validateProblemAndParameters() (defined in SVM) | SVM | protected |
| validateSVMType(UINT svmType) (defined in SVM) | SVM | 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 |
| ~Classifier(void) | Classifier | 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 |
| ~SVM() | SVM | virtual |
1.8.11 
