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.
Classifier Member List

This is the complete list of members for Classifier, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
BaseTypes enum name (defined in MLBase)MLBase
bestDistance (defined in Classifier)Classifierprotected
classDistances (defined in Classifier)Classifierprotected
Classifier(void)Classifier
CLASSIFIER enum value (defined in MLBase)MLBase
classifierMode (defined in Classifier)Classifierprotected
ClassifierModes enum name (defined in Classifier)Classifier
classifierType (defined in Classifier)Classifierprotected
classLabels (defined in Classifier)Classifierprotected
classLikelihoods (defined in Classifier)Classifierprotected
classType (defined in GRTBase)GRTBaseprotected
clear()Classifiervirtual
CLUSTERER enum value (defined in MLBase)MLBase
copyBaseVariables(const Classifier *classifier)Classifier
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
createInstanceFromString(std::string const &classifierType)Classifierstatic
createNewInstance() const Classifier
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Classifier
deepCopyFrom(const Classifier *classifier)Classifierinlinevirtual
enableNullRejection(bool useNullRejection)Classifier
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
getBaseClassifier() const Classifier
getBaseType() const MLBase
getBestDistance() const Classifier
getClassDistances() const Classifier
getClassifierPointer() const Classifier
getClassifierType() const Classifier
getClassLabelIndexValue(UINT classLabel) const Classifier
getClassLabels() const Classifier
getClassLikelihoods() const Classifier
getClassType() const GRTBase
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
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()Classifierinlineprotectedstatic
getMaximumLikelihood() const Classifier
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getModelTrained() const MLBase
getNullRejectionCoeff() const Classifier
getNullRejectionEnabled() const Classifier
getNullRejectionThresholds() const Classifier
getNumClasses() const Classifiervirtual
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()Classifierstatic
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getSupportsNullRejection() const Classifier
getTimeseriesCompatible() const Classifierinline
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)GRTBaseprotected
inputType (defined in MLBase)MLBaseprotected
learningRate (defined in MLBase)MLBaseprotected
load(const std::string filename)MLBasevirtual
load(std::fstream &file)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)Classifierprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxLikelihood (defined in Classifier)Classifierprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(void)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)Classifierprotected
nullRejectionThresholds (defined in Classifier)Classifierprotected
numClasses (defined in Classifier)Classifierprotected
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (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
outputType (defined in MLBase)MLBaseprotected
phase (defined in Classifier)Classifierprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)MLBasevirtual
predict_(MatrixFloat &inputMatrix)MLBasevirtual
predictedClassLabel (defined in Classifier)Classifierprotected
print() const MLBasevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
ranges (defined in Classifier)Classifierprotected
recomputeNullRejectionThresholds()Classifierinlinevirtual
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()Classifiervirtual
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(const std::string filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const Classifierprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)MLBaseinline
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
setNullRejectionCoeff(Float nullRejectionCoeff)Classifiervirtual
setNullRejectionThresholds(VectorFloat newRejectionThresholds)Classifiervirtual
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)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)GRTBaseinlineprotected
STANDARD_CLASSIFIER_MODE enum value (defined in Classifier)Classifier
StringClassifierMap typedefClassifier
supportsNullRejection (defined in Classifier)Classifierprotected
testingLog (defined in GRTBase)GRTBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
TIMESERIES_CLASSIFIER_MODE enum value (defined in Classifier)Classifier
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)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_(TimeSeriesClassificationData &trainingData)MLBasevirtual
train_(ClassificationDataStream &trainingData)MLBasevirtual
train_(UnlabelledData &trainingData)MLBasevirtual
train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
useNullRejection (defined in Classifier)Classifierprotected
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
~Classifier(void)Classifiervirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual