GestureRecognitionToolkit  Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
Regressifier Member List

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

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
BaseType enum name (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
batchSize (defined in MLBase)MLBaseprotected
classIdGRTBaseprotected
CLASSIFIER enum value (defined in MLBase)MLBase
clear() overrideRegressifiervirtual
CLUSTERER enum value (defined in MLBase)MLBase
CONTEXT enum value (defined in MLBase)MLBase
converged (defined in MLBase)MLBaseprotected
copyBaseVariables(const Regressifier *regressifier)Regressifier
copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
create(const std::string &id)Regressifierstatic
create() const Regressifier
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Regressifier
deepCopyFrom(const Regressifier *regressifier)Regressifierinlinevirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
FEATURE_EXTRACTION enum value (defined in MLBase)MLBase
getBaseRegressifier() const Regressifier
getBatchSize() const MLBase
getConverged() const MLBase
getGRTBasePointer()GRTBase
getGRTBasePointer() const GRTBase
getGRTRevison()GRTBasestatic
getGRTVersion(bool returnRevision=true)GRTBasestatic
getId() const GRTBase
getInputRanges() const Regressifier
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 Regressifier)Regressifierinlineprotectedstatic
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumRestarts() const MLBase
getNumTrainingIterationsToConverge() const MLBase
getOutputRanges() const Regressifier
getOutputType() const MLBase
getRandomiseTrainingOrder() const MLBase
getRegisteredRegressifiers()Regressifierstatic
getRegressionData() const Regressifier
getRMSTrainingError() const MLBase
getRMSValidationError() const MLBase
getScalingEnabled() const MLBase
getTestingLoggingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingLoggingEnabled() const MLBase
getTrainingResults() const MLBase
getType() const MLBase
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
GRT_DEPRECATED_MSG("createNewInstance is deprecated, use create() instead.", Regressifier *createNewInstance() const ) (defined in Regressifier)Regressifier
GRT_DEPRECATED_MSG("createInstanceFromString(id) is deprecated, use create(id) instead.", static Regressifier *createInstanceFromString(const std::string &id)) (defined in Regressifier)Regressifier
GRT_DEPRECATED_MSG("getRegressifierType is deprecated, use getId() instead", std::string getRegressifierType() const ) (defined in Regressifier)Regressifier
MLBase::GRT_DEPRECATED_MSG("saveModelToFile(std::string filename) is deprecated, use save(const std::string &filename) instead", virtual bool saveModelToFile(const std::string &filename) const )MLBase
MLBase::GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )MLBase
MLBase::GRT_DEPRECATED_MSG("loadModelFromFile(std::string filename) is deprecated, use load(const std::string &filename) instead", virtual bool loadModelFromFile(const std::string &filename))MLBase
MLBase::GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))MLBase
MLBase::GRT_DEPRECATED_MSG("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )MLBase
MLBase::GRT_DEPRECATED_MSG("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const )MLBase
GRTBase::GRT_DEPRECATED_MSG("getClassType is deprecated, use getId() instead!", std::string getClassType() const )GRTBase
GRTBase(const std::string &id="")GRTBase
infoLog (defined in GRTBase)GRTBaseprotected
inputType (defined in MLBase)MLBaseprotected
inputVectorRanges (defined in Regressifier)Regressifierprotected
learningRate (defined in MLBase)MLBaseprotected
load(const std::string &filename)MLBasevirtual
load(std::fstream &file)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)Regressifierprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
MLBase(const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)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
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numRestarts (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
POST_PROCESSING enum value (defined in MLBase)MLBase
PRE_PROCSSING enum value (defined in MLBase)MLBase
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)MLBasevirtual
predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const MLBasevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
registerTestResultsObserver(Observer< TestInstanceResult > &observer)MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)MLBase
Regressifier(const std::string &id="")Regressifier
REGRESSIFIER enum value (defined in MLBase)MLBase
regressifierType (defined in Regressifier)Regressifierprotected
regressionData (defined in Regressifier)Regressifierprotected
removeAllTestObservers()MLBase
removeAllTrainingObservers()MLBase
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)MLBase
reset() overrideRegressifiervirtual
rmsTrainingError (defined in MLBase)MLBaseprotected
rmsValidationError (defined in MLBase)MLBaseprotected
save(const std::string &filename) const MLBasevirtual
save(std::fstream &file) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const Regressifierprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)GRTBaseinline
setBatchSize(const UINT batchSize)MLBase
setDebugLoggingEnabled(const bool loggingEnabled)GRTBase
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
setNumRestarts(const UINT numRestarts)MLBase
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setTestingLoggingEnabled(const bool loggingEnabled)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)GRTBaseinline
StringRegressifierMap typedefRegressifier
targetVectorRanges (defined in Regressifier)Regressifierprotected
testingLog (defined in MLBase)MLBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(RegressionData trainingData, RegressionData validationData)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_(RegressionData &trainingData, RegressionData &validationData)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 MLBase)MLBaseprotected
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
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
~Regressifier(void)Regressifiervirtual