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.
GaussianMixtureModels Member List

This is the complete list of members for GaussianMixtureModels, 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 Clusterer)Clustererprotected
CLASSIFIER enum value (defined in MLBase)MLBase
classType (defined in GRTBase)GRTBaseprotected
clear()GaussianMixtureModelsvirtual
clusterDistances (defined in Clusterer)Clustererprotected
Clusterer(void)Clusterer
CLUSTERER enum value (defined in MLBase)MLBase
clustererType (defined in Clusterer)Clustererprotected
clusterLabels (defined in Clusterer)Clustererprotected
clusterLikelihoods (defined in Clusterer)Clustererprotected
computeInvAndDet() (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
converged (defined in Clusterer)Clustererprotected
copyBaseVariables(const Clusterer *clusterer)Clusterer
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
createInstanceFromString(std::string const &ClustererType)Clustererstatic
createNewInstance() const Clusterer
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Clusterer
deepCopyFrom(const Clusterer *clusterer)GaussianMixtureModelsvirtual
det (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
estep(const MatrixFloat &data, VectorDouble &u, VectorDouble &v, Float &change) (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
fracGaussianMixtureModelsprotected
gauss(const VectorDouble &x, const UINT clusterIndex, const VectorDouble &det, const MatrixFloat &mu, const Vector< MatrixFloat > &invSigma) (defined in GaussianMixtureModels)GaussianMixtureModelsinlineprotected
GaussianMixtureModels(const UINT numClusters=10, const UINT minNumEpochs=5, const UINT maxNumEpochs=1000, const Float minChange=1.0e-5)GaussianMixtureModels
GaussianMixtureModels(const GaussianMixtureModels &rhs)GaussianMixtureModels
getBaseClusterer() const Clusterer
getBaseType() const MLBase
getBestDistance() const Clusterer
getClassType() const GRTBase
getClusterDistances() const Clusterer
getClustererType() const Clusterer
getClusterLabels() const Clusterer
getClusterLikelihoods() const Clusterer
getConverged() const Clusterer
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() (defined in Clusterer)Clustererinlineprotectedstatic
getMaximumLikelihood() const Clusterer
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
getMu() const GaussianMixtureModelsinline
getNumClusters() const Clusterer
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumTrainingIterationsToConverge() const MLBase
getOutputType() const MLBase
getPredictedClusterLabel() const Clusterer
getRandomiseTrainingOrder() const MLBase
getRegisteredClusterers()Clustererstatic
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getSigma() const GaussianMixtureModelsinline
getSigma(const UINT k) const GaussianMixtureModelsinline
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
invSigma (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
learningRate (defined in MLBase)MLBaseprotected
lndetsGaussianMixtureModelsprotected
load(const std::string filename)MLBasevirtual
load(std::fstream &file)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)MLBaseprotected
loadClustererSettingsFromFile(std::fstream &file)Clustererprotected
loadModelFromFile(std::fstream &file)GaussianMixtureModelsvirtual
loglikeGaussianMixtureModelsprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxLikelihood (defined in Clusterer)Clustererprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(void)MLBase
mstep(const MatrixFloat &data) (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
muGaussianMixtureModelsprotected
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
numClustersClustererprotected
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
numTrainingSamplesGaussianMixtureModelsprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
operator=(const GaussianMixtureModels &rhs)GaussianMixtureModels
outputType (defined in MLBase)MLBaseprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorDouble &inputVector)GaussianMixtureModelsvirtual
Clusterer::predict_(MatrixFloat &inputMatrix)MLBasevirtual
predictedClusterLabelClustererprotected
print() const MLBasevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
ranges (defined in Clusterer)Clustererprotected
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()GaussianMixtureModelsvirtual
respGaussianMixtureModelsprotected
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(const std::string filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
saveClustererSettingsToFile(std::fstream &file) const Clustererprotected
saveModelToFile(std::fstream &file) const GaussianMixtureModelsvirtual
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
setNumClusters(const UINT numClusters)Clusterer
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
sigma (defined in GaussianMixtureModels)GaussianMixtureModelsprotected
SQR(const Float v) (defined in GaussianMixtureModels)GaussianMixtureModelsinlineprotected
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
StringClustererMap typedefClusterer
SWAP(UINT &a, UINT &b) (defined in GaussianMixtureModels)GaussianMixtureModelsinlineprotected
testingLog (defined in GRTBase)GRTBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
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_(MatrixFloat &trainingData)GaussianMixtureModelsvirtual
train_(ClassificationData &trainingData)GaussianMixtureModelsvirtual
train_(UnlabelledData &trainingData)GaussianMixtureModelsvirtual
MLBase::train_(RegressionData &trainingData)MLBasevirtual
MLBase::train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
MLBase::train_(ClassificationDataStream &trainingData)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
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
~Clusterer(void)Clusterervirtual
~GaussianMixtureModels()GaussianMixtureModelsvirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual