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.
FFTFeatures Member List

This is the complete list of members for FFTFeatures, 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)MLBaseprotected
batchSize (defined in MLBase)MLBaseprotected
centroidFeature (defined in FFTFeatures)FFTFeaturesprotected
classIdGRTBaseprotected
CLASSIFIER enum value (defined in MLBase)MLBase
clear() overrideFeatureExtractionvirtual
CLUSTERER enum value (defined in MLBase)MLBase
computeCentroidFeature (defined in FFTFeatures)FFTFeaturesprotected
computeFeatures(const VectorFloat &inputVector)FFTFeaturesvirtual
FeatureExtraction::computeFeatures(const MatrixFloat &inputMatrix)FeatureExtractioninlinevirtual
computeMaxFreqFeature (defined in FFTFeatures)FFTFeaturesprotected
computeMaxFreqSpectrumRatio (defined in FFTFeatures)FFTFeaturesprotected
computeTopNFreqFeatures (defined in FFTFeatures)FFTFeaturesprotected
CONTEXT enum value (defined in MLBase)MLBase
converged (defined in MLBase)MLBaseprotected
copyBaseVariables(const FeatureExtraction *featureExtractionModule)FeatureExtraction
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
create(const std::string &id) (defined in FeatureExtraction)FeatureExtractionstatic
create() const FeatureExtraction
debugLog (defined in GRTBase)GRTBaseprotected
deepCopyFrom(const FeatureExtraction *featureExtraction)FFTFeaturesvirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
FEATURE_EXTRACTION enum value (defined in MLBase)MLBase
featureDataReady (defined in FeatureExtraction)FeatureExtractionprotected
FeatureExtraction(const std::string id="")FeatureExtraction
featureExtractionType (defined in FeatureExtraction)FeatureExtractionprotected
featureMatrix (defined in FeatureExtraction)FeatureExtractionprotected
featureVector (defined in FeatureExtraction)FeatureExtractionprotected
FFTFeatures(const UINT fftWindowSize=512, const UINT numChannelsInFFTSignal=1, const bool computeMaxFreqFeature=true, const bool computeMaxFreqSpectrumRatio=true, const bool computeCentroidFeature=true, const bool computeTopNFreqFeatures=true, const UINT N=10)FFTFeatures
FFTFeatures(const FFTFeatures &rhs)FFTFeatures
fftWindowSize (defined in FFTFeatures)FFTFeaturesprotected
getBatchSize() const MLBase
getConverged() const MLBase
getFeatureDataReady() const FeatureExtraction
getFeatureMatrix() const FeatureExtraction
getFeatureVector() const FeatureExtraction
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
getId()FFTFeaturesstatic
FeatureExtraction::getId() const GRTBase
getInitialized() const FeatureExtraction
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
getLastErrorMessage() const GRTBase
getLastInfoMessage() const GRTBase
getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMap() (defined in FeatureExtraction)FeatureExtractioninlineprotectedstatic
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumRestarts() const MLBase
getNumTrainingIterationsToConverge() const MLBase
getOutputType() const MLBase
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("createNewInstance is deprecated, use create() instead.", FeatureExtraction *createNewInstance() const ) (defined in FeatureExtraction)FeatureExtraction
GRT_DEPRECATED_MSG("createInstanceFromString(id) is deprecated, use create(id) instead.", static FeatureExtraction *createInstanceFromString(const std::string &id)) (defined in FeatureExtraction)FeatureExtraction
GRT_DEPRECATED_MSG("getFeatureExtractionType is deprecated, use getId() instead", std::string getFeatureExtractionType() const ) (defined in FeatureExtraction)FeatureExtraction
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)GRTBaseprotected
init(const UINT fftWindowSize, const UINT numChannelsInFFTSignal, const bool computeMaxFreqFeature, const bool computeMaxFreqSpectrumRatio, const bool computeCentroidFeature, const bool computeTopNFreqFeatures, const UINT N)FFTFeatures
FeatureExtraction::init()FeatureExtractionprotected
initialized (defined in FeatureExtraction)FeatureExtractionprotected
inputType (defined in MLBase)MLBaseprotected
learningRate (defined in MLBase)MLBaseprotected
load(std::fstream &file)FFTFeaturesvirtual
FeatureExtraction::load(const std::string &filename)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)MLBaseprotected
loadFeatureExtractionSettingsFromFile(std::fstream &file)FeatureExtractionprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxFreqFeature (defined in FFTFeatures)FFTFeaturesprotected
maxFreqSpectrumRatio (defined in FFTFeatures)FFTFeaturesprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)MLBase
N (defined in FFTFeatures)FFTFeaturesprotected
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
numChannelsInFFTSignal (defined in FFTFeatures)FFTFeaturesprotected
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numRestarts (defined in MLBase)MLBaseprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
operator=(const FFTFeatures &rhs)FFTFeatures
outputType (defined in MLBase)MLBaseprotected
POST_PROCESSING enum value (defined in MLBase)MLBase
PRE_PROCSSING enum value (defined in MLBase)MLBase
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)MLBasevirtual
predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const MLBasevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
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()FFTFeaturesvirtual
rmsTrainingError (defined in MLBase)MLBaseprotected
rmsValidationError (defined in MLBase)MLBaseprotected
save(std::fstream &file) const FFTFeaturesvirtual
FeatureExtraction::save(const std::string &filename) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
saveFeatureExtractionSettingsToFile(std::fstream &file) const FeatureExtractionprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)GRTBaseinline
setBatchSize(const UINT batchSize)MLBase
setDebugLoggingEnabled(const bool loggingEnabled)GRTBase
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
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)GRTBaseinline
StringFeatureExtractionMap typedefFeatureExtraction
testingLog (defined in MLBase)MLBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
topNFreqFeatures (defined in FFTFeatures)FFTFeaturesprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(RegressionData trainingData, RegressionData validationData)MLBasevirtual
train(TimeSeriesClassificationData trainingData)MLBasevirtual
train(ClassificationDataStream trainingData)MLBasevirtual
train(UnlabelledData trainingData)MLBasevirtual
train(MatrixFloat data)MLBasevirtual
train_(ClassificationData &trainingData)MLBasevirtual
train_(RegressionData &trainingData)MLBasevirtual
train_(RegressionData &trainingData, RegressionData &validationData)MLBasevirtual
train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
train_(ClassificationDataStream &trainingData)MLBasevirtual
train_(UnlabelledData &trainingData)MLBasevirtual
train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in MLBase)MLBaseprotected
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
useScaling (defined in MLBase)MLBaseprotected
useValidationSet (defined in MLBase)MLBaseprotected
validationSetAccuracy (defined in MLBase)MLBaseprotected
validationSetPrecision (defined in MLBase)MLBaseprotected
validationSetRecall (defined in MLBase)MLBaseprotected
validationSetSize (defined in MLBase)MLBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
~FeatureExtraction()FeatureExtractionvirtual
~FFTFeatures(void)FFTFeaturesvirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual