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GestureRecognitionToolkit
Version: 1.0 Revision: 04-03-15
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 GRT::RegisterPostProcessingModule< T >, including all inherited members.
BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase) | GRT::MLBase | private |
baseType (defined in GRT::MLBase) | GRT::MLBase | private |
BaseTypes enum name (defined in GRT::MLBase) | GRT::MLBase | private |
CLASSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | private |
classType (defined in GRT::GRTBase) | GRT::GRTBase | private |
clear() | GRT::MLBase | privatevirtual |
CLUSTERER enum value (defined in GRT::MLBase) | GRT::MLBase | private |
copyBaseVariables(const PostProcessing *postProcessingModule) | GRT::PostProcessing | private |
copyGRTBaseVariables(const GRTBase *GRTBase) | GRT::GRTBase | private |
copyMLBaseVariables(const MLBase *mlBase) | GRT::MLBase | private |
createInstanceFromString(string const &postProcessingType) | GRT::PostProcessing | privatestatic |
createNewInstance() const | GRT::PostProcessing | private |
debugLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
deepCopyFrom(const PostProcessing *postProcessing) | GRT::PostProcessing | inlineprivatevirtual |
enableScaling(bool useScaling) | GRT::MLBase | private |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
getBaseType() const | GRT::MLBase | private |
getClassType() const | GRT::GRTBase | private |
getGRTBasePointer() | GRT::GRTBase | private |
getGRTBasePointer() const | GRT::GRTBase | private |
getGRTRevison() | GRT::GRTBase | privatestatic |
getGRTVersion(bool returnRevision=true) | GRT::GRTBase | privatestatic |
getInitialized() const | GRT::PostProcessing | private |
getIsBaseTypeClassifier() const | GRT::MLBase | private |
getIsBaseTypeClusterer() const | GRT::MLBase | private |
getIsBaseTypeRegressifier() const | GRT::MLBase | private |
getIsPostProcessingInputModeClassLikelihoods() const | GRT::PostProcessing | private |
getIsPostProcessingInputModePredictedClassLabel() const | GRT::PostProcessing | private |
getIsPostProcessingOutputModeClassLikelihoods() const | GRT::PostProcessing | private |
getIsPostProcessingOutputModePredictedClassLabel() const | GRT::PostProcessing | private |
getLastErrorMessage() const | GRT::GRTBase | private |
getLastInfoMessage() const | GRT::GRTBase | private |
getLastWarningMessage() const | GRT::GRTBase | private |
getLearningRate() const | GRT::MLBase | private |
getMap() (defined in GRT::PostProcessing) | GRT::PostProcessing | inlineprivatestatic |
getMaxNumEpochs() const | GRT::MLBase | private |
getMinChange() const | GRT::MLBase | private |
getMinNumEpochs() const | GRT::MLBase | private |
getMLBasePointer() | GRT::MLBase | private |
getMLBasePointer() const | GRT::MLBase | private |
getModel(ostream &stream) const | GRT::MLBase | privatevirtual |
getModelAsString() const | GRT::MLBase | privatevirtual |
getModelTrained() const | GRT::MLBase | private |
getNumInputDimensions() const | GRT::PostProcessing | private |
getNumInputFeatures() const | GRT::MLBase | private |
getNumOutputDimensions() const | GRT::PostProcessing | private |
getNumTrainingIterationsToConverge() const | GRT::MLBase | private |
getPostProcessingInputMode() const | GRT::PostProcessing | private |
getPostProcessingOutputMode() const | GRT::PostProcessing | private |
getPostProcessingType() const | GRT::PostProcessing | private |
getProcessedData() const | GRT::PostProcessing | private |
getRandomiseTrainingOrder() const | GRT::MLBase | private |
getRootMeanSquaredTrainingError() const | GRT::MLBase | private |
getScalingEnabled() const | GRT::MLBase | private |
getTotalSquaredTrainingError() const | GRT::MLBase | private |
getTrained() const | GRT::MLBase | private |
getTrainingResults() const | GRT::MLBase | private |
getUseValidationSet() const | GRT::MLBase | private |
getValidationSetSize() const | GRT::MLBase | private |
GRTBase(void) | GRT::GRTBase | private |
infoLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
init() | GRT::PostProcessing | private |
initialized (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
INPUT_MODE_CLASS_LIKELIHOODS enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
INPUT_MODE_NOT_SET enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
INPUT_MODE_PREDICTED_CLASS_LABEL enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
learningRate (defined in GRT::MLBase) | GRT::MLBase | private |
load(const string filename) | GRT::MLBase | privatevirtual |
loadBaseSettingsFromFile(fstream &file) | GRT::MLBase | private |
loadModelFromFile(string filename) | GRT::PostProcessing | privatevirtual |
loadModelFromFile(fstream &file) | GRT::PostProcessing | inlineprivatevirtual |
loadPostProcessingSettingsFromFile(fstream &file) | GRT::PostProcessing | private |
map(VectorDouble inputVector) | GRT::MLBase | privatevirtual |
map_(VectorDouble &inputVector) | GRT::MLBase | privatevirtual |
maxNumEpochs (defined in GRT::MLBase) | GRT::MLBase | private |
minChange (defined in GRT::MLBase) | GRT::MLBase | private |
minNumEpochs (defined in GRT::MLBase) | GRT::MLBase | private |
MLBase(void) | GRT::MLBase | private |
notify(const TrainingResult &data) (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlineprivatevirtual |
notify(const TestInstanceResult &data) (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlineprivatevirtual |
notifyTestResultsObservers(const TestInstanceResult &data) | GRT::MLBase | private |
notifyTrainingResultsObservers(const TrainingResult &data) | GRT::MLBase | private |
numInputDimensions (defined in GRT::MLBase) | GRT::MLBase | private |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | private |
numTrainingIterationsToConverge (defined in GRT::MLBase) | GRT::MLBase | private |
Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlineprivate |
Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlineprivate |
OUTPUT_MODE_CLASS_LIKELIHOODS enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
OUTPUT_MODE_NOT_SET enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
OUTPUT_MODE_PREDICTED_CLASS_LABEL enum value (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
PostProcessing(void) | GRT::PostProcessing | private |
postProcessingInputMode (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
PostprocessingInputModes enum name (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
postProcessingOutputMode (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
PostprocessingOutputModes enum name (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
postProcessingType (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
predict(VectorDouble inputVector) | GRT::MLBase | privatevirtual |
predict(MatrixDouble inputMatrix) | GRT::MLBase | privatevirtual |
predict_(VectorDouble &inputVector) | GRT::MLBase | privatevirtual |
predict_(MatrixDouble &inputMatrix) | GRT::MLBase | privatevirtual |
print() const | GRT::MLBase | privatevirtual |
process(const VectorDouble &inputVector) | GRT::PostProcessing | inlineprivatevirtual |
processedData (defined in GRT::PostProcessing) | GRT::PostProcessing | private |
random (defined in GRT::MLBase) | GRT::MLBase | private |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | private |
RegisterPostProcessingModule(string const &newPostProcessingModuleName) (defined in GRT::RegisterPostProcessingModule< T >) | GRT::RegisterPostProcessingModule< T > | inline |
registerTestResultsObserver(Observer< TestInstanceResult > &observer) | GRT::MLBase | private |
registerTrainingResultsObserver(Observer< TrainingResult > &observer) | GRT::MLBase | private |
REGRESSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | private |
removeAllTestObservers() | GRT::MLBase | private |
removeAllTrainingObservers() | GRT::MLBase | private |
removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | GRT::MLBase | private |
removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | GRT::MLBase | private |
reset() | GRT::PostProcessing | inlineprivatevirtual |
rootMeanSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | private |
save(const string filename) const | GRT::MLBase | privatevirtual |
saveBaseSettingsToFile(fstream &file) const | GRT::MLBase | private |
saveModelToFile(string filename) const | GRT::PostProcessing | privatevirtual |
saveModelToFile(fstream &file) const | GRT::PostProcessing | inlineprivatevirtual |
savePostProcessingSettingsToFile(fstream &file) const | GRT::PostProcessing | private |
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false) | GRT::MLBase | inlineprivate |
setLearningRate(double learningRate) | GRT::MLBase | private |
setMaxNumEpochs(const UINT maxNumEpochs) | GRT::MLBase | private |
setMinChange(const double minChange) | GRT::MLBase | private |
setMinNumEpochs(const UINT minNumEpochs) | GRT::MLBase | private |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | GRT::MLBase | private |
setUseValidationSet(const bool useValidationSet) | GRT::MLBase | private |
setValidationSetSize(const UINT validationSetSize) | GRT::MLBase | private |
SQR(const double &x) const (defined in GRT::GRTBase) | GRT::GRTBase | inlineprivate |
StringPostProcessingMap typedef | GRT::PostProcessing | private |
testingLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
testResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | private |
totalSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | private |
train(ClassificationData trainingData) | GRT::MLBase | privatevirtual |
train(RegressionData trainingData) | GRT::MLBase | privatevirtual |
train(TimeSeriesClassificationData trainingData) | GRT::MLBase | privatevirtual |
train(TimeSeriesClassificationDataStream trainingData) | GRT::MLBase | privatevirtual |
train(UnlabelledData trainingData) | GRT::MLBase | privatevirtual |
train(MatrixDouble data) | GRT::MLBase | privatevirtual |
train_(ClassificationData &trainingData) | GRT::MLBase | privatevirtual |
train_(RegressionData &trainingData) | GRT::MLBase | privatevirtual |
train_(TimeSeriesClassificationData &trainingData) | GRT::MLBase | privatevirtual |
train_(TimeSeriesClassificationDataStream &trainingData) | GRT::MLBase | privatevirtual |
train_(UnlabelledData &trainingData) | GRT::MLBase | privatevirtual |
train_(MatrixDouble &data) | GRT::MLBase | privatevirtual |
trained (defined in GRT::MLBase) | GRT::MLBase | private |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
trainingResults (defined in GRT::MLBase) | GRT::MLBase | private |
trainingResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | private |
useScaling (defined in GRT::MLBase) | GRT::MLBase | private |
useValidationSet (defined in GRT::MLBase) | GRT::MLBase | private |
validationSetSize (defined in GRT::MLBase) | GRT::MLBase | private |
warningLog (defined in GRT::GRTBase) | GRT::GRTBase | private |
~GRTBase(void) | GRT::GRTBase | privatevirtual |
~MLBase(void) | GRT::MLBase | privatevirtual |
~Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlineprivatevirtual |
~Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlineprivatevirtual |
~PostProcessing(void) | GRT::PostProcessing | privatevirtual |