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.
BernoulliRBM Member List

This is the complete list of members for BernoulliRBM, 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
BatchIndexs typedef (defined in BernoulliRBM)BernoulliRBMprotected
batchSize (defined in BernoulliRBM)BernoulliRBMprotected
batchStepSize (defined in BernoulliRBM)BernoulliRBMprotected
BernoulliRBM(const UINT numHiddenUnits=100, const UINT maxNumEpochs=1000, const Float learningRate=1, const Float learningRateUpdate=1, const Float momentum=0.5, const bool useScaling=true, const bool randomiseTrainingOrder=true) (defined in BernoulliRBM)BernoulliRBM
CLASSIFIER enum value (defined in MLBase)MLBase
classType (defined in GRTBase)GRTBaseprotected
clear()BernoulliRBMvirtual
CLUSTERER enum value (defined in MLBase)MLBase
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
debugLog (defined in GRTBase)GRTBaseprotected
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
getBaseType() const MLBase
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
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
getNumHiddenUnits() const (defined in BernoulliRBM)BernoulliRBM
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumTrainingIterationsToConverge() const MLBase
getNumVisibleUnits() const (defined in BernoulliRBM)BernoulliRBM
getOutputData() const (defined in BernoulliRBM)BernoulliRBM
getOutputType() const MLBase
getRandomiseTrainingOrder() const MLBase
getRandomizeWeightsForTraining() const (defined in BernoulliRBM)BernoulliRBM
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingResults() const MLBase
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
getWeights() const (defined in BernoulliRBM)BernoulliRBM
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
hiddenLayerBias (defined in BernoulliRBM)BernoulliRBMprotected
infoLog (defined in GRTBase)GRTBaseprotected
inputType (defined in MLBase)MLBaseprotected
learningRate (defined in MLBase)MLBaseprotected
learningRateUpdate (defined in BernoulliRBM)BernoulliRBMprotected
load(std::fstream &file)BernoulliRBMvirtual
MLBase::load(const std::string filename)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)MLBaseprotected
loadLegacyModelFromFile(std::fstream &file)BernoulliRBMprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(void)MLBase
momentum (defined in BernoulliRBM)BernoulliRBMprotected
nh_means (defined in BernoulliRBM)BernoulliRBMprotected
nh_samples (defined in BernoulliRBM)BernoulliRBMprotected
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
numHiddenUnits (defined in BernoulliRBM)BernoulliRBMprotected
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
numVisibleUnits (defined in BernoulliRBM)BernoulliRBMprotected
nv_means (defined in BernoulliRBM)BernoulliRBMprotected
nv_samples (defined in BernoulliRBM)BernoulliRBMprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
outputData (defined in BernoulliRBM)BernoulliRBMprotected
outputType (defined in MLBase)MLBaseprotected
ph_mean (defined in BernoulliRBM)BernoulliRBMprotected
ph_sample (defined in BernoulliRBM)BernoulliRBMprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputData)BernoulliRBMvirtual
predict_(VectorFloat &inputData, VectorFloat &outputData)BernoulliRBM
predict_(const MatrixFloat &inputData, MatrixFloat &outputData, const UINT rowIndex)BernoulliRBM
MLBase::predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const BernoulliRBMvirtual
rand (defined in BernoulliRBM)BernoulliRBMprotected
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
randomizeWeightsForTraining (defined in BernoulliRBM)BernoulliRBMprotected
ranges (defined in BernoulliRBM)BernoulliRBMprotected
reconstruct(const VectorFloat &input, VectorFloat &output) (defined in BernoulliRBM)BernoulliRBM
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()BernoulliRBMvirtual
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(std::fstream &file) const BernoulliRBMvirtual
MLBase::save(const std::string filename) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const MLBaseprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)MLBaseinline
setBatchSize(const UINT batchSize) (defined in BernoulliRBM)BernoulliRBM
setBatchStepSize(const UINT batchStepSize) (defined in BernoulliRBM)BernoulliRBM
setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
setLearningRate(const Float learningRate)MLBase
setLearningRateUpdate(const Float learningRateUpdate) (defined in BernoulliRBM)BernoulliRBM
setMaxNumEpochs(const UINT maxNumEpochs)MLBase
setMinChange(const Float minChange)MLBase
setMinNumEpochs(const UINT minNumEpochs)MLBase
setMomentum(const Float momentum) (defined in BernoulliRBM)BernoulliRBM
setNumHiddenUnits(const UINT numHiddenUnits) (defined in BernoulliRBM)BernoulliRBM
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setRandomizeWeightsForTraining(const bool randomizeWeightsForTraining) (defined in BernoulliRBM)BernoulliRBM
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
sigmoidRandom(const Float &x) (defined in BernoulliRBM)BernoulliRBMinlineprotected
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
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 &data)BernoulliRBMvirtual
MLBase::train_(ClassificationData &trainingData)MLBasevirtual
MLBase::train_(RegressionData &trainingData)MLBasevirtual
MLBase::train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
MLBase::train_(ClassificationDataStream &trainingData)MLBasevirtual
MLBase::train_(UnlabelledData &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
visibleLayerBias (defined in BernoulliRBM)BernoulliRBMprotected
warningLog (defined in GRTBase)GRTBaseprotected
weightsMatrix (defined in BernoulliRBM)BernoulliRBMprotected
~BernoulliRBM() (defined in BernoulliRBM)BernoulliRBMvirtual
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual