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.
GRT::GaussianMixtureModels Member List

This is the complete list of members for GRT::GaussianMixtureModels, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase)GRT::MLBase
baseType (defined in GRT::MLBase)GRT::MLBaseprotected
BaseTypes enum name (defined in GRT::MLBase)GRT::MLBase
bestDistance (defined in GRT::Clusterer)GRT::Clustererprotected
CLASSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
classType (defined in GRT::GRTBase)GRT::GRTBaseprotected
clear()GRT::GaussianMixtureModelsvirtual
clusterDistances (defined in GRT::Clusterer)GRT::Clustererprotected
Clusterer(void)GRT::Clusterer
CLUSTERER enum value (defined in GRT::MLBase)GRT::MLBase
clustererType (defined in GRT::Clusterer)GRT::Clustererprotected
clusterLabels (defined in GRT::Clusterer)GRT::Clustererprotected
clusterLikelihoods (defined in GRT::Clusterer)GRT::Clustererprotected
computeInvAndDet() (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
converged (defined in GRT::Clusterer)GRT::Clustererprotected
copyBaseVariables(const Clusterer *Clusterer)GRT::Clusterer
copyGRTBaseVariables(const GRTBase *GRTBase)GRT::GRTBase
copyMLBaseVariables(const MLBase *mlBase)GRT::MLBase
createInstanceFromString(string const &ClustererType)GRT::Clustererstatic
createNewInstance() const GRT::Clusterer
debugLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
deepCopy() const GRT::Clusterer
deepCopyFrom(const Clusterer *clusterer)GRT::GaussianMixtureModelsvirtual
det (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
enableScaling(bool useScaling)GRT::MLBase
errorLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
estep(const MatrixDouble &data, VectorDouble &u, VectorDouble &v, double &change) (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
fracGRT::GaussianMixtureModelsprotected
gauss(const VectorDouble &x, const UINT clusterIndex, const VectorDouble &det, const MatrixDouble &mu, const vector< MatrixDouble > &invSigma) (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsinlineprotected
GaussianMixtureModels(const UINT numClusters=10, const UINT minNumEpochs=5, const UINT maxNumEpochs=1000, const double minChange=1.0e-5)GRT::GaussianMixtureModels
GaussianMixtureModels(const GaussianMixtureModels &rhs)GRT::GaussianMixtureModels
getBaseClusterer() const GRT::Clusterer
getBaseType() const GRT::MLBase
getBestDistance() const GRT::Clusterer
getClassType() const GRT::GRTBase
getClusterDistances() const GRT::Clusterer
getClustererType() const GRT::Clusterer
getClusterLabels() const GRT::Clusterer
getClusterLikelihoods() const GRT::Clusterer
getConverged() const GRT::Clusterer
getGRTBasePointer()GRT::GRTBase
getGRTBasePointer() const GRT::GRTBase
getGRTRevison()GRT::GRTBasestatic
getGRTVersion(bool returnRevision=true)GRT::GRTBasestatic
getIsBaseTypeClassifier() const GRT::MLBase
getIsBaseTypeClusterer() const GRT::MLBase
getIsBaseTypeRegressifier() const GRT::MLBase
getLastErrorMessage() const GRT::GRTBase
getLastInfoMessage() const GRT::GRTBase
getLastWarningMessage() const GRT::GRTBase
getLearningRate() const GRT::MLBase
getMap() (defined in GRT::Clusterer)GRT::Clustererinlineprotectedstatic
getMaximumLikelihood() const GRT::Clusterer
getMaxNumEpochs() const GRT::MLBase
getMinChange() const GRT::MLBase
getMinNumEpochs() const GRT::MLBase
getMLBasePointer()GRT::MLBase
getMLBasePointer() const GRT::MLBase
getModel(ostream &stream) const GRT::MLBasevirtual
getModelAsString() const GRT::MLBasevirtual
getModelTrained() const GRT::MLBase
getMu() const GRT::GaussianMixtureModelsinline
getNumClusters() const GRT::Clusterer
getNumInputDimensions() const GRT::MLBase
getNumInputFeatures() const GRT::MLBase
getNumOutputDimensions() const GRT::MLBase
getNumTrainingIterationsToConverge() const GRT::MLBase
getPredictedClusterLabel() const GRT::Clusterer
getRandomiseTrainingOrder() const GRT::MLBase
getRegisteredClusterers()GRT::Clustererstatic
getRootMeanSquaredTrainingError() const GRT::MLBase
getScalingEnabled() const GRT::MLBase
getSigma() const GRT::GaussianMixtureModelsinline
getSigma(const UINT k) const GRT::GaussianMixtureModelsinline
getTotalSquaredTrainingError() const GRT::MLBase
getTrained() const GRT::MLBase
getTrainingResults() const GRT::MLBase
getUseValidationSet() const GRT::MLBase
getValidationSetSize() const GRT::MLBase
GRTBase(void)GRT::GRTBase
infoLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
invSigma (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
learningRate (defined in GRT::MLBase)GRT::MLBaseprotected
lndetsGRT::GaussianMixtureModelsprotected
load(const string filename)GRT::MLBasevirtual
loadBaseSettingsFromFile(fstream &file)GRT::MLBaseprotected
loadClustererSettingsFromFile(fstream &file)GRT::Clustererprotected
loadModelFromFile(fstream &file)GRT::GaussianMixtureModelsvirtual
GRT::Clusterer::loadModelFromFile(string filename)GRT::MLBasevirtual
loglikeGRT::GaussianMixtureModelsprotected
map(VectorDouble inputVector)GRT::MLBasevirtual
map_(VectorDouble &inputVector)GRT::MLBasevirtual
maxLikelihood (defined in GRT::Clusterer)GRT::Clustererprotected
maxNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
minChange (defined in GRT::MLBase)GRT::MLBaseprotected
minNumEpochs (defined in GRT::MLBase)GRT::MLBaseprotected
MLBase(void)GRT::MLBase
mstep(const MatrixDouble &data) (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
muGRT::GaussianMixtureModelsprotected
notify(const TrainingResult &data) (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inlinevirtual
notify(const TestInstanceResult &data) (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inlinevirtual
notifyTestResultsObservers(const TestInstanceResult &data)GRT::MLBase
notifyTrainingResultsObservers(const TrainingResult &data)GRT::MLBase
numClustersGRT::Clustererprotected
numInputDimensions (defined in GRT::MLBase)GRT::MLBaseprotected
numOutputDimensions (defined in GRT::MLBase)GRT::MLBaseprotected
numTrainingIterationsToConverge (defined in GRT::MLBase)GRT::MLBaseprotected
numTrainingSamplesGRT::GaussianMixtureModelsprotected
Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inline
Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inline
operator=(const GaussianMixtureModels &rhs)GRT::GaussianMixtureModels
predict(VectorDouble inputVector)GRT::MLBasevirtual
predict(MatrixDouble inputMatrix)GRT::MLBasevirtual
predict_(VectorDouble &inputVector)GRT::GaussianMixtureModelsvirtual
GRT::Clusterer::predict_(MatrixDouble &inputMatrix)GRT::MLBasevirtual
predictedClusterLabelGRT::Clustererprotected
print() const GRT::MLBasevirtual
random (defined in GRT::MLBase)GRT::MLBaseprotected
randomiseTrainingOrder (defined in GRT::MLBase)GRT::MLBaseprotected
ranges (defined in GRT::Clusterer)GRT::Clustererprotected
registerTestResultsObserver(Observer< TestInstanceResult > &observer)GRT::MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)GRT::MLBase
REGRESSIFIER enum value (defined in GRT::MLBase)GRT::MLBase
removeAllTestObservers()GRT::MLBase
removeAllTrainingObservers()GRT::MLBase
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)GRT::MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)GRT::MLBase
reset()GRT::GaussianMixtureModelsvirtual
respGRT::GaussianMixtureModelsprotected
rootMeanSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
save(const string filename) const GRT::MLBasevirtual
saveBaseSettingsToFile(fstream &file) const GRT::MLBaseprotected
saveClustererSettingsToFile(fstream &file) const GRT::Clustererprotected
saveModelToFile(fstream &file) const GRT::GaussianMixtureModelsvirtual
GRT::Clusterer::saveModelToFile(string filename) const GRT::MLBasevirtual
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false)GRT::MLBaseinline
setLearningRate(double learningRate)GRT::MLBase
setMaxNumEpochs(const UINT maxNumEpochs)GRT::MLBase
setMinChange(const double minChange)GRT::MLBase
setMinNumEpochs(const UINT minNumEpochs)GRT::MLBase
setNumClusters(const UINT numClusters)GRT::Clusterer
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)GRT::MLBase
setUseValidationSet(const bool useValidationSet)GRT::MLBase
setValidationSetSize(const UINT validationSetSize)GRT::MLBase
sigma (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsprotected
SQR(const double v) (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsinlineprotected
SQR(const double &x) const (defined in GRT::GRTBase)GRT::GRTBaseinlineprotected
StringClustererMap typedefGRT::Clusterer
SWAP(UINT &a, UINT &b) (defined in GRT::GaussianMixtureModels)GRT::GaussianMixtureModelsinlineprotected
testingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
testResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
totalSquaredTrainingError (defined in GRT::MLBase)GRT::MLBaseprotected
train(ClassificationData trainingData)GRT::MLBasevirtual
train(RegressionData trainingData)GRT::MLBasevirtual
train(TimeSeriesClassificationData trainingData)GRT::MLBasevirtual
train(TimeSeriesClassificationDataStream trainingData)GRT::MLBasevirtual
train(UnlabelledData trainingData)GRT::MLBasevirtual
train(MatrixDouble data)GRT::MLBasevirtual
train_(MatrixDouble &data)GRT::GaussianMixtureModelsvirtual
train_(ClassificationData &trainingData)GRT::GaussianMixtureModelsvirtual
train_(UnlabelledData &trainingData)GRT::GaussianMixtureModelsvirtual
GRT::MLBase::train_(RegressionData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(TimeSeriesClassificationData &trainingData)GRT::MLBasevirtual
GRT::MLBase::train_(TimeSeriesClassificationDataStream &trainingData)GRT::MLBasevirtual
trained (defined in GRT::MLBase)GRT::MLBaseprotected
trainingLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
trainingResults (defined in GRT::MLBase)GRT::MLBaseprotected
trainingResultsObserverManager (defined in GRT::MLBase)GRT::MLBaseprotected
useScaling (defined in GRT::MLBase)GRT::MLBaseprotected
useValidationSet (defined in GRT::MLBase)GRT::MLBaseprotected
validationSetSize (defined in GRT::MLBase)GRT::MLBaseprotected
warningLog (defined in GRT::GRTBase)GRT::GRTBaseprotected
~Clusterer(void)GRT::Clusterervirtual
~GaussianMixtureModels()GRT::GaussianMixtureModelsvirtual
~GRTBase(void)GRT::GRTBasevirtual
~MLBase(void)GRT::MLBasevirtual
~Observer() (defined in GRT::Observer< TrainingResult >)GRT::Observer< TrainingResult >inlinevirtual
~Observer() (defined in GRT::Observer< TestInstanceResult >)GRT::Observer< TestInstanceResult >inlinevirtual