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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 KNN, including all inherited members.
| 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 |
| bestDistance (defined in Classifier) | Classifier | protected |
| classDistances (defined in Classifier) | Classifier | protected |
| classId | GRTBase | protected |
| Classifier(const std::string &classifierId="") | Classifier | |
| CLASSIFIER enum value (defined in MLBase) | MLBase | |
| classifierMode (defined in Classifier) | Classifier | protected |
| ClassifierModes enum name (defined in Classifier) | Classifier | |
| classLabels (defined in Classifier) | Classifier | protected |
| classLikelihoods (defined in Classifier) | Classifier | protected |
| clear() | KNN | virtual |
| CLUSTERER enum value (defined in MLBase) | MLBase | |
| computeAccuracy(const ClassificationData &data, Float &accuracy) | Classifier | virtual |
| computeCosineDistance(const VectorFloat &a, const VectorFloat &b) (defined in KNN) | KNN | protected |
| computeEuclideanDistance(const VectorFloat &a, const VectorFloat &b) (defined in KNN) | KNN | protected |
| computeManhattanDistance(const VectorFloat &a, const VectorFloat &b) (defined in KNN) | KNN | protected |
| CONTEXT enum value (defined in MLBase) | MLBase | |
| converged (defined in MLBase) | MLBase | protected |
| copyBaseVariables(const Classifier *classifier) | Classifier | |
| copyGRTBaseVariables(const GRTBase *GRTBase) | GRTBase | |
| copyMLBaseVariables(const MLBase *mlBase) | MLBase | |
| COSINE_DISTANCE enum value (defined in KNN) | KNN | |
| create(const std::string &id) | Classifier | static |
| create() const | Classifier | |
| debugLog (defined in GRTBase) | GRTBase | protected |
| deepCopy() const | Classifier | |
| deepCopyFrom(const Classifier *classifier) | KNN | virtual |
| distanceMethod | KNN | protected |
| DistanceMethods enum name (defined in KNN) | KNN | |
| enableBestKValueSearch(bool searchForBestKValue) | KNN | |
| enableNullRejection(const bool useNullRejection) | Classifier | |
| enableScaling(const bool useScaling) | MLBase | |
| errorLog (defined in GRTBase) | GRTBase | protected |
| EUCLIDEAN_DISTANCE enum value (defined in KNN) | KNN | |
| FEATURE_EXTRACTION enum value (defined in MLBase) | MLBase | |
| getBaseClassifier() const | Classifier | |
| getBatchSize() const | MLBase | |
| getBestDistance() const | Classifier | |
| getClassDistances() const | Classifier | |
| getClassifierPointer() const | Classifier | |
| getClassifierType() const | Classifier | |
| getClassLabelIndexValue(const UINT classLabel) const | Classifier | |
| getClassLabels() const | Classifier | |
| getClassLikelihoods() const | Classifier | |
| getConverged() const | MLBase | |
| getDistanceMethod() | KNN | inline |
| getGRTBasePointer() | GRTBase | |
| getGRTBasePointer() const | GRTBase | |
| getGRTRevison() | GRTBase | static |
| getGRTVersion(bool returnRevision=true) | GRTBase | static |
| getId() | KNN | static |
| Classifier::getId() const | GRTBase | |
| getInputType() const | MLBase | |
| getIsBaseTypeClassifier() const | MLBase | |
| getIsBaseTypeClusterer() const | MLBase | |
| getIsBaseTypeRegressifier() const | MLBase | |
| getK() | KNN | inline |
| 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(std::ostream &stream) const | MLBase | virtual |
| getModelAsString() const | MLBase | virtual |
| getNullRejectionCoeff() const | Classifier | |
| getNullRejectionEnabled() const | Classifier | |
| getNullRejectionThresholds() const | Classifier | |
| getNumClasses() const | Classifier | virtual |
| getNumInputDimensions() const | MLBase | |
| getNumInputFeatures() const | MLBase | |
| getNumOutputDimensions() const | MLBase | |
| getNumRestarts() const | MLBase | |
| getNumTrainingIterationsToConverge() const | MLBase | |
| getOutputType() const | MLBase | |
| getPhase() const | Classifier | |
| getPredictedClassLabel() const | Classifier | |
| getRandomiseTrainingOrder() const | MLBase | |
| getRanges() const | Classifier | |
| getRegisteredClassifiers() | Classifier | static |
| getRMSTrainingError() const | MLBase | |
| getRMSValidationError() const | MLBase | |
| getScalingEnabled() const | MLBase | |
| getSupportsNullRejection() const | Classifier | |
| getTestingLoggingEnabled() const | MLBase | |
| getTimeseriesCompatible() const | Classifier | inline |
| getTotalSquaredTrainingError() const | MLBase | |
| getTrained() const | MLBase | |
| getTrainingLoggingEnabled() const | MLBase | |
| getTrainingResults() const | MLBase | |
| getTrainingSetAccuracy() const | Classifier | |
| getType() const | MLBase | |
| getUseValidationSet() const | MLBase | |
| getValidationSetAccuracy() const | MLBase | |
| getValidationSetPrecision() const | MLBase | |
| getValidationSetRecall() const | MLBase | |
| getValidationSetSize() const | MLBase | |
| GRT_DEPRECATED_MSG("createNewInstance is deprecated, use create instead.", Classifier *createNewInstance() const ) (defined in Classifier) | Classifier | |
| GRT_DEPRECATED_MSG("createInstanceFromString is deprecated, use create instead.", static Classifier *createInstanceFromString(const std::string &id)) (defined in Classifier) | Classifier | |
| 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 | |
| MLBase::GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const ) | MLBase | |
| 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 | |
| MLBase::GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file)) | MLBase | |
| MLBase::GRT_DEPRECATED_MSG("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const ) | MLBase | |
| 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 |
| K (defined in KNN) | KNN | protected |
| KNN(UINT K=10, bool useScaling=false, bool useNullRejection=false, Float nullRejectionCoeff=10.0, bool searchForBestKValue=false, UINT minKSearchValue=1, UINT maxKSearchValue=10) | KNN | |
| KNN(const KNN &rhs) | KNN | |
| learningRate (defined in MLBase) | MLBase | protected |
| load(std::fstream &file) | KNN | virtual |
| Classifier::load(const std::string &filename) | MLBase | virtual |
| loadBaseSettingsFromFile(std::fstream &file) | Classifier | protected |
| loadLegacyModelFromFile(std::fstream &file) | KNN | protected |
| MANHATTAN_DISTANCE enum value (defined in KNN) | KNN | |
| map(VectorFloat inputVector) | MLBase | virtual |
| map_(VectorFloat &inputVector) | MLBase | virtual |
| maxKSearchValue | KNN | protected |
| maxLikelihood (defined in Classifier) | Classifier | protected |
| maxNumEpochs (defined in MLBase) | MLBase | protected |
| minChange (defined in MLBase) | MLBase | protected |
| minKSearchValue | KNN | protected |
| minNumEpochs (defined in MLBase) | MLBase | protected |
| MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET) | MLBase | |
| 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 | |
| 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 |
| numRestarts (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 |
| operator=(const KNN &rhs) | KNN | |
| outputType (defined in MLBase) | MLBase | protected |
| phase (defined in Classifier) | Classifier | protected |
| POST_PROCESSING enum value (defined in MLBase) | MLBase | |
| PRE_PROCSSING enum value (defined in MLBase) | MLBase | |
| predict(const VectorFloat &inputVector, const UINT K) (defined in KNN) | KNN | protected |
| Classifier::predict(VectorFloat inputVector) | MLBase | virtual |
| Classifier::predict(MatrixFloat inputMatrix) | MLBase | virtual |
| predict_(VectorFloat &inputVector) | KNN | virtual |
| Classifier::predict_(MatrixFloat &inputMatrix) | MLBase | virtual |
| predictedClassLabel (defined in Classifier) | Classifier | protected |
| print() const | MLBase | virtual |
| random (defined in MLBase) | MLBase | protected |
| randomiseTrainingOrder (defined in MLBase) | MLBase | protected |
| ranges (defined in Classifier) | Classifier | protected |
| recomputeNullRejectionThresholds() | KNN | virtual |
| 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 |
| rmsTrainingError (defined in MLBase) | MLBase | protected |
| rmsValidationError (defined in MLBase) | MLBase | protected |
| save(std::fstream &file) const | KNN | 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) | GRTBase | inline |
| searchForBestKValue | KNN | protected |
| setBatchSize(const UINT batchSize) | MLBase | |
| setDebugLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setDistanceMethod(UINT distanceMethod) | KNN | |
| setErrorLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setInfoLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setK(UINT K) | KNN | |
| setLearningRate(const Float learningRate) | MLBase | |
| setMaxKSearchValue(UINT maxKSearchValue) | KNN | |
| setMaxNumEpochs(const UINT maxNumEpochs) | MLBase | |
| setMinChange(const Float minChange) | MLBase | |
| setMinKSearchValue(UINT minKSearchValue) | KNN | |
| setMinNumEpochs(const UINT minNumEpochs) | MLBase | |
| setNullRejectionCoeff(Float nullRejectionCoeff) | KNN | virtual |
| setNullRejectionThresholds(const VectorFloat &newRejectionThresholds) | Classifier | virtual |
| setNumRestarts(const UINT numRestarts) | MLBase | |
| setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | MLBase | |
| 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 | |
| SQR(const Float &x) const (defined in GRTBase) | GRTBase | inline |
| STANDARD_CLASSIFIER_MODE enum value (defined in Classifier) | Classifier | |
| StringClassifierMap typedef | Classifier | |
| supportsNullRejection (defined in Classifier) | Classifier | protected |
| testingLog (defined in MLBase) | MLBase | 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(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_(ClassificationData &trainingData) | KNN | virtual |
| train_(const ClassificationData &trainingData, const UINT K) (defined in KNN) | KNN | protected |
| Classifier::train_(RegressionData &trainingData) | MLBase | virtual |
| Classifier::train_(RegressionData &trainingData, RegressionData &validationData) | 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 |
| trainingData | KNN | protected |
| trainingLog (defined in MLBase) | MLBase | protected |
| trainingMu | KNN | protected |
| trainingResults (defined in MLBase) | MLBase | protected |
| trainingResultsObserverManager (defined in MLBase) | MLBase | protected |
| trainingSetAccuracy (defined in Classifier) | Classifier | protected |
| trainingSigma | KNN | protected |
| useNullRejection (defined in Classifier) | Classifier | 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 |
| ~Classifier(void) | Classifier | virtual |
| ~GRTBase(void) | GRTBase | virtual |
| ~KNN(void) | KNN | virtual |
| ~MLBase(void) | MLBase | virtual |
| ~Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlinevirtual |
| ~Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlinevirtual |
1.8.11 
