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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::BernoulliRBM, including all inherited members.
BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase) | GRT::MLBase | |
baseType (defined in GRT::MLBase) | GRT::MLBase | protected |
BaseTypes enum name (defined in GRT::MLBase) | GRT::MLBase | |
BatchIndexs typedef (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
batchSize (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
batchStepSize (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
BernoulliRBM(const UINT numHiddenUnits=100, const UINT maxNumEpochs=1000, const double learningRate=1, const double learningRateUpdate=1, const double momentum=0.5, const bool useScaling=true, const bool randomiseTrainingOrder=true) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
CLASSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
classType (defined in GRT::GRTBase) | GRT::GRTBase | protected |
clear() | GRT::BernoulliRBM | virtual |
CLUSTERER enum value (defined in GRT::MLBase) | GRT::MLBase | |
copyGRTBaseVariables(const GRTBase *GRTBase) | GRT::GRTBase | |
copyMLBaseVariables(const MLBase *mlBase) | GRT::MLBase | |
debugLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
enableScaling(bool useScaling) | GRT::MLBase | |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
getBaseType() const | GRT::MLBase | |
getClassType() const | GRT::GRTBase | |
getGRTBasePointer() | GRT::GRTBase | |
getGRTBasePointer() const | GRT::GRTBase | |
getGRTRevison() | GRT::GRTBase | static |
getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
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 | |
getMaxNumEpochs() const | GRT::MLBase | |
getMinChange() const | GRT::MLBase | |
getMinNumEpochs() const | GRT::MLBase | |
getMLBasePointer() | GRT::MLBase | |
getMLBasePointer() const | GRT::MLBase | |
getModel(ostream &stream) const | GRT::MLBase | virtual |
getModelAsString() const | GRT::MLBase | virtual |
getModelTrained() const | GRT::MLBase | |
getNumHiddenUnits() const (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
getNumInputDimensions() const | GRT::MLBase | |
getNumInputFeatures() const | GRT::MLBase | |
getNumOutputDimensions() const | GRT::MLBase | |
getNumTrainingIterationsToConverge() const | GRT::MLBase | |
getNumVisibleUnits() const (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
getOutputData() const (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
getRandomiseTrainingOrder() const | GRT::MLBase | |
getRandomizeWeightsForTraining() const (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
getRootMeanSquaredTrainingError() const | GRT::MLBase | |
getScalingEnabled() const | GRT::MLBase | |
getTotalSquaredTrainingError() const | GRT::MLBase | |
getTrained() const | GRT::MLBase | |
getTrainingResults() const | GRT::MLBase | |
getUseValidationSet() const | GRT::MLBase | |
getValidationSetSize() const | GRT::MLBase | |
getWeights() const (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
GRTBase(void) | GRT::GRTBase | |
hiddenLayerBias (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
infoLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
learningRate (defined in GRT::MLBase) | GRT::MLBase | protected |
learningRateUpdate (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
load(const string filename) | GRT::MLBase | virtual |
loadBaseSettingsFromFile(fstream &file) | GRT::MLBase | protected |
loadLegacyModelFromFile(fstream &file) | GRT::BernoulliRBM | protected |
loadModelFromFile(fstream &file) | GRT::BernoulliRBM | virtual |
GRT::MLBase::loadModelFromFile(string filename) | GRT::MLBase | virtual |
map(VectorDouble inputVector) | GRT::MLBase | virtual |
map_(VectorDouble &inputVector) | GRT::MLBase | virtual |
maxNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
minChange (defined in GRT::MLBase) | GRT::MLBase | protected |
minNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
MLBase(void) | GRT::MLBase | |
momentum (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
nh_means (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
nh_samples (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
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 | |
numHiddenUnits (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
numInputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numTrainingIterationsToConverge (defined in GRT::MLBase) | GRT::MLBase | protected |
numVisibleUnits (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
nv_means (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
nv_samples (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inline |
Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inline |
outputData (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
ph_mean (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
ph_sample (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
predict(VectorDouble inputVector) | GRT::MLBase | virtual |
predict(MatrixDouble inputMatrix) | GRT::MLBase | virtual |
predict_(VectorDouble &inputData) | GRT::BernoulliRBM | virtual |
predict_(VectorDouble &inputData, VectorDouble &outputData) | GRT::BernoulliRBM | |
predict_(const MatrixDouble &inputData, MatrixDouble &outputData, const UINT rowIndex) | GRT::BernoulliRBM | |
GRT::MLBase::predict_(MatrixDouble &inputMatrix) | GRT::MLBase | virtual |
print() const | GRT::BernoulliRBM | virtual |
rand (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
random (defined in GRT::MLBase) | GRT::MLBase | protected |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | protected |
randomizeWeightsForTraining (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
ranges (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
reconstruct(const VectorDouble &input, VectorDouble &output) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
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::BernoulliRBM | virtual |
rootMeanSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
save(const string filename) const | GRT::MLBase | virtual |
saveBaseSettingsToFile(fstream &file) const | GRT::MLBase | protected |
saveModelToFile(fstream &file) const | GRT::BernoulliRBM | virtual |
GRT::MLBase::saveModelToFile(string filename) const | GRT::MLBase | virtual |
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false) | GRT::MLBase | inline |
setBatchSize(const UINT batchSize) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setBatchStepSize(const UINT batchStepSize) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setLearningRate(double learningRate) | GRT::MLBase | |
setLearningRateUpdate(const double learningRateUpdate) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setMaxNumEpochs(const UINT maxNumEpochs) | GRT::MLBase | |
setMinChange(const double minChange) | GRT::MLBase | |
setMinNumEpochs(const UINT minNumEpochs) | GRT::MLBase | |
setMomentum(const double momentum) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setNumHiddenUnits(const UINT numHiddenUnits) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | GRT::MLBase | |
setRandomizeWeightsForTraining(const bool randomizeWeightsForTraining) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | |
setUseValidationSet(const bool useValidationSet) | GRT::MLBase | |
setValidationSetSize(const UINT validationSetSize) | GRT::MLBase | |
sigmoid(const double &x) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | inlineprotected |
sigmoidRandom(const double &x) (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | inlineprotected |
SQR(const double &x) const (defined in GRT::GRTBase) | GRT::GRTBase | inlineprotected |
testingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
testResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
totalSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
train(ClassificationData trainingData) | GRT::MLBase | virtual |
train(RegressionData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationDataStream trainingData) | GRT::MLBase | virtual |
train(UnlabelledData trainingData) | GRT::MLBase | virtual |
train(MatrixDouble data) | GRT::MLBase | virtual |
train_(MatrixDouble &data) | GRT::BernoulliRBM | virtual |
GRT::MLBase::train_(ClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(RegressionData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(TimeSeriesClassificationData &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(TimeSeriesClassificationDataStream &trainingData) | GRT::MLBase | virtual |
GRT::MLBase::train_(UnlabelledData &trainingData) | GRT::MLBase | virtual |
trained (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
trainingResults (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
useScaling (defined in GRT::MLBase) | GRT::MLBase | protected |
useValidationSet (defined in GRT::MLBase) | GRT::MLBase | protected |
validationSetSize (defined in GRT::MLBase) | GRT::MLBase | protected |
visibleLayerBias (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
warningLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
weightsMatrix (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | protected |
~BernoulliRBM() (defined in GRT::BernoulliRBM) | GRT::BernoulliRBM | virtual |
~GRTBase(void) | GRT::GRTBase | virtual |
~MLBase(void) | GRT::MLBase | virtual |
~Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlinevirtual |
~Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlinevirtual |