FiniteStateMachine Class Reference

#include <FiniteStateMachine.h>

Inheritance diagram for FiniteStateMachine:

Public Member Functions
	FiniteStateMachine (const UINT numParticles=200, const UINT numClustersPerState=20, const Float stateTransitionSmoothingCoeff=0.0, const Float measurementNoise=10.0)
	FiniteStateMachine (const FiniteStateMachine &rhs)
virtual	~FiniteStateMachine (void)
FiniteStateMachine &	operator= (const FiniteStateMachine &rhs)
virtual bool	deepCopyFrom (const Classifier *classifier)
virtual bool	train_ (ClassificationData &trainingData)
virtual bool	train_ (TimeSeriesClassificationData &trainingData)
virtual bool	train_ (TimeSeriesClassificationDataStream &data)
virtual bool	predict_ (VectorFloat &inputVector)
virtual bool	reset ()
virtual bool	clear ()
virtual bool	print () const
virtual bool	save (std::fstream &file) const
virtual bool	load (std::fstream &file)
bool	setNumParticles (const UINT numParticles)
bool	setNumClustersPerState (const UINT numClustersPerState)
bool	setStateTransitionSmoothingCoeff (const Float stateTransitionSmoothingCoeff)
bool	setMeasurementNoise (const Float measurementNoise)
Public Member Functions inherited from Classifier
	Classifier (const std::string &classifierId="")
virtual	~Classifier (void)
bool	copyBaseVariables (const Classifier *classifier)
virtual bool	computeAccuracy (const ClassificationData &data, Float &accuracy)
std::string	getClassifierType () const
bool	getSupportsNullRejection () const
bool	getNullRejectionEnabled () const
Float	getNullRejectionCoeff () const
Float	getMaximumLikelihood () const
Float	getBestDistance () const
Float	getPhase () const
Float	getTrainingSetAccuracy () const
virtual UINT	getNumClasses () const
UINT	getClassLabelIndexValue (const UINT classLabel) const
UINT	getPredictedClassLabel () const
VectorFloat	getClassLikelihoods () const
VectorFloat	getClassDistances () const
VectorFloat	getNullRejectionThresholds () const
Vector< UINT >	getClassLabels () const
Vector< MinMax >	getRanges () const
bool	enableNullRejection (const bool useNullRejection)
virtual bool	setNullRejectionCoeff (const Float nullRejectionCoeff)
virtual bool	setNullRejectionThresholds (const VectorFloat &newRejectionThresholds)
virtual bool	recomputeNullRejectionThresholds ()
bool	getTimeseriesCompatible () const
Classifier *	create () const
	GRT_DEPRECATED_MSG ("createNewInstance is deprecated, use create instead.", Classifier *createNewInstance() const )
	GRT_DEPRECATED_MSG ("createInstanceFromString is deprecated, use create instead.", static Classifier *createInstanceFromString(const std::string &id))
Classifier *	deepCopy () const
const Classifier *	getClassifierPointer () const
const Classifier &	getBaseClassifier () const
Public Member Functions inherited from MLBase
	MLBase (const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)
virtual	~MLBase (void)
bool	copyMLBaseVariables (const MLBase *mlBase)
virtual bool	train (ClassificationData trainingData)
virtual bool	train (RegressionData trainingData)
virtual bool	train_ (RegressionData &trainingData)
virtual bool	train (RegressionData trainingData, RegressionData validationData)
virtual bool	train_ (RegressionData &trainingData, RegressionData &validationData)
virtual bool	train (TimeSeriesClassificationData trainingData)
virtual bool	train (ClassificationDataStream trainingData)
virtual bool	train (UnlabelledData trainingData)
virtual bool	train_ (UnlabelledData &trainingData)
virtual bool	train (MatrixFloat data)
virtual bool	train_ (MatrixFloat &data)
virtual bool	predict (VectorFloat inputVector)
virtual bool	predict (MatrixFloat inputMatrix)
virtual bool	predict_ (MatrixFloat &inputMatrix)
virtual bool	map (VectorFloat inputVector)
virtual bool	map_ (VectorFloat &inputVector)
virtual bool	save (const std::string &filename) const
virtual bool	load (const std::string &filename)
	GRT_DEPRECATED_MSG ("saveModelToFile(std::string filename) is deprecated, use save(const std::string &filename) instead", virtual bool saveModelToFile(const std::string &filename) const )
	GRT_DEPRECATED_MSG ("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )
	GRT_DEPRECATED_MSG ("loadModelFromFile(std::string filename) is deprecated, use load(const std::string &filename) instead", virtual bool loadModelFromFile(const std::string &filename))
	GRT_DEPRECATED_MSG ("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))
virtual bool	getModel (std::ostream &stream) const
virtual std::string	getModelAsString () const
DataType	getInputType () const
DataType	getOutputType () const
BaseType	getType () const
UINT	getNumInputFeatures () const
UINT	getNumInputDimensions () const
UINT	getNumOutputDimensions () const
UINT	getMinNumEpochs () const
UINT	getMaxNumEpochs () const
UINT	getBatchSize () const
UINT	getNumRestarts () const
UINT	getValidationSetSize () const
UINT	getNumTrainingIterationsToConverge () const
Float	getMinChange () const
Float	getLearningRate () const
Float	getRMSTrainingError () const
	GRT_DEPRECATED_MSG ("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )
Float	getTotalSquaredTrainingError () const
Float	getRMSValidationError () const
Float	getValidationSetAccuracy () const
VectorFloat	getValidationSetPrecision () const
VectorFloat	getValidationSetRecall () const
bool	getUseValidationSet () const
bool	getRandomiseTrainingOrder () const
bool	getTrained () const
	GRT_DEPRECATED_MSG ("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const )
bool	getConverged () const
bool	getScalingEnabled () const
bool	getIsBaseTypeClassifier () const
bool	getIsBaseTypeRegressifier () const
bool	getIsBaseTypeClusterer () const
bool	getTrainingLoggingEnabled () const
bool	getTestingLoggingEnabled () const
bool	enableScaling (const bool useScaling)
bool	setMaxNumEpochs (const UINT maxNumEpochs)
bool	setBatchSize (const UINT batchSize)
bool	setMinNumEpochs (const UINT minNumEpochs)
bool	setNumRestarts (const UINT numRestarts)
bool	setMinChange (const Float minChange)
bool	setLearningRate (const Float learningRate)
bool	setUseValidationSet (const bool useValidationSet)
bool	setValidationSetSize (const UINT validationSetSize)
bool	setRandomiseTrainingOrder (const bool randomiseTrainingOrder)
bool	setTrainingLoggingEnabled (const bool loggingEnabled)
bool	setTestingLoggingEnabled (const bool loggingEnabled)
bool	registerTrainingResultsObserver (Observer< TrainingResult > &observer)
bool	registerTestResultsObserver (Observer< TestInstanceResult > &observer)
bool	removeTrainingResultsObserver (const Observer< TrainingResult > &observer)
bool	removeTestResultsObserver (const Observer< TestInstanceResult > &observer)
bool	removeAllTrainingObservers ()
bool	removeAllTestObservers ()
bool	notifyTrainingResultsObservers (const TrainingResult &data)
bool	notifyTestResultsObservers (const TestInstanceResult &data)
MLBase *	getMLBasePointer ()
const MLBase *	getMLBasePointer () const
Vector< TrainingResult >	getTrainingResults () const
Public Member Functions inherited from GRTBase
	GRTBase (const std::string &id="")
virtual	~GRTBase (void)
bool	copyGRTBaseVariables (const GRTBase *GRTBase)
	GRT_DEPRECATED_MSG ("getClassType is deprecated, use getId() instead!", std::string getClassType() const )
std::string	getId () const
std::string	getLastWarningMessage () const
std::string	getLastErrorMessage () const
std::string	getLastInfoMessage () const
bool	setInfoLoggingEnabled (const bool loggingEnabled)
bool	setWarningLoggingEnabled (const bool loggingEnabled)
bool	setErrorLoggingEnabled (const bool loggingEnabled)
bool	setDebugLoggingEnabled (const bool loggingEnabled)
GRTBase *	getGRTBasePointer ()
const GRTBase *	getGRTBasePointer () const
Float	scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)
Float	SQR (const Float &x) const
Public Member Functions inherited from Observer< TrainingResult >
virtual void	notify (const TrainingResult &data)
Public Member Functions inherited from Observer< TestInstanceResult >
virtual void	notify (const TestInstanceResult &data)

Static Public Member Functions
static std::string	getId ()
Static Public Member Functions inherited from Classifier
static Classifier *	create (const std::string &id)
static Vector< std::string >	getRegisteredClassifiers ()
Static Public Member Functions inherited from GRTBase
static std::string	getGRTVersion (bool returnRevision=true)
static std::string	getGRTRevison ()

Protected Member Functions
bool	recomputePT ()
bool	recomputePE ()
bool	initParticles ()
Protected Member Functions inherited from Classifier
bool	saveBaseSettingsToFile (std::fstream &file) const
bool	loadBaseSettingsFromFile (std::fstream &file)
Protected Member Functions inherited from MLBase
bool	saveBaseSettingsToFile (std::fstream &file) const
bool	loadBaseSettingsFromFile (std::fstream &file)

Protected Attributes
UINT	numParticles
UINT	numClustersPerState
Float	stateTransitionSmoothingCoeff
Float	measurementNoise
FSMParticleFilter	particles
MatrixFloat	stateTransitions
Vector< MatrixFloat >	stateEmissions
Vector< Vector< IndexedDouble > >	pt
	This stores the stateTransitions matrix in a format more efficient for the particle filter.
Vector< Vector< VectorFloat > >	pe
	This stores the stateEmissions model in a format more efficient for the particle filter.
Protected Attributes inherited from Classifier
bool	supportsNullRejection
bool	useNullRejection
UINT	numClasses
UINT	predictedClassLabel
UINT	classifierMode
Float	nullRejectionCoeff
Float	maxLikelihood
Float	bestDistance
Float	phase
Float	trainingSetAccuracy
VectorFloat	classLikelihoods
VectorFloat	classDistances
VectorFloat	nullRejectionThresholds
Vector< UINT >	classLabels
Vector< MinMax >	ranges
Protected Attributes inherited from MLBase
bool	trained
bool	useScaling
bool	converged
DataType	inputType
DataType	outputType
BaseType	baseType
UINT	numInputDimensions
UINT	numOutputDimensions
UINT	numTrainingIterationsToConverge
UINT	minNumEpochs
UINT	maxNumEpochs
UINT	batchSize
UINT	validationSetSize
UINT	numRestarts
Float	learningRate
Float	minChange
Float	rmsTrainingError
Float	rmsValidationError
Float	totalSquaredTrainingError
Float	validationSetAccuracy
bool	useValidationSet
bool	randomiseTrainingOrder
VectorFloat	validationSetPrecision
VectorFloat	validationSetRecall
Random	random
Vector< TrainingResult >	trainingResults
TrainingResultsObserverManager	trainingResultsObserverManager
TestResultsObserverManager	testResultsObserverManager
TrainingLog	trainingLog
TestingLog	testingLog
Protected Attributes inherited from GRTBase
std::string	classId
	Stores the name of the class (e.g., MinDist)
DebugLog	debugLog
ErrorLog	errorLog
InfoLog	infoLog
WarningLog	warningLog

Additional Inherited Members
Public Types inherited from Classifier
enum	ClassifierModes { STANDARD_CLASSIFIER_MODE =0, TIMESERIES_CLASSIFIER_MODE }
typedef std::map< std::string, Classifier *(*)() >	StringClassifierMap
Public Types inherited from MLBase
enum	BaseType {   BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER,   PRE_PROCSSING, POST_PROCESSING, FEATURE_EXTRACTION, CONTEXT }
Static Protected Member Functions inherited from Classifier
static StringClassifierMap *	getMap ()

Detailed Description

GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Definition at line 35 of file FiniteStateMachine.h.

Constructor & Destructor Documentation

FiniteStateMachine::FiniteStateMachine	(	const UINT	numParticles = 200,
		const UINT	numClustersPerState = 20,
		const Float	stateTransitionSmoothingCoeff = 0.0,
		const Float	measurementNoise = 10.0
	)

Default constructor.

Definition at line 33 of file FiniteStateMachine.cpp.

FiniteStateMachine::FiniteStateMachine

(

const FiniteStateMachine &

rhs

)

Defines the copy constructor.

Parameters

rhs	the instance from which all the data will be copied into this instance

Definition at line 47 of file FiniteStateMachine.cpp.

FiniteStateMachine::~FiniteStateMachine ( void  )

virtual

Default Destructor

Definition at line 53 of file FiniteStateMachine.cpp.

Member Function Documentation

bool FiniteStateMachine::clear ( )

virtual

This overrides the clear function in the Classifier base class. It will completely clear the ML module, removing any trained model and setting all the base variables to their default values.

Returns

returns true if the module was cleared succesfully, false otherwise

Reimplemented from Classifier.

Definition at line 340 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::deepCopyFrom ( const Classifier *  classifier )

virtual

This is required for the Gesture Recognition Pipeline for when the pipeline.setClassifier(...) method is called. It clones the data from the Base Class Classifier pointer (which should be pointing to an FiniteStateMachine instance) into this instance

Parameters

classifier

a pointer to the Classifier Base Class, this should be pointing to another FiniteStateMachine instance

Returns

returns true if the clone was successfull, false otherwise

Reimplemented from Classifier.

Definition at line 81 of file FiniteStateMachine.cpp.

std::string FiniteStateMachine::getId ( )

static

Gets a string that represents the FiniteStateMachine class.

Returns

returns a string containing the ID of this class

Definition at line 28 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::load ( std::fstream &  file )

virtual

This loads a trained FiniteStateMachine model from a file. This overrides the load function in the Classifier base class.

Parameters

file	a reference to the file the FiniteStateMachine model will be loaded from

Returns

returns true if the model was loaded successfully, false otherwise

Reimplemented from MLBase.

Definition at line 436 of file FiniteStateMachine.cpp.

FiniteStateMachine & FiniteStateMachine::operator=

(

const FiniteStateMachine &

rhs

)

Defines how the data from the rhs FPSM should be copied to this FPSM

Parameters

rhs	another instance of a FPSM

Returns

returns a pointer to this instance of the FPSM

Definition at line 57 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::predict_ ( VectorFloat &  inputVector )

virtual

This predicts the class of the inputVector. This overrides the predict function in the Classifier base class.

Parameters

inputVector

the input vector to classify

Returns

returns true if the prediction was performed, false otherwise

Reimplemented from MLBase.

Definition at line 274 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::print ( ) const

virtual

This overrides the print function in the Classifier base class. It will print the current model and settings to the infoLog.

Returns

returns true if the module was cleared succesfully, false otherwise

Reimplemented from MLBase.

Definition at line 355 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::reset ( )

virtual

This resets the FiniteStateMachine.

If a model has been trained then this will randomize the current state and reset all the particles.

Returns

returns true if the FPSM model was successfully reset, false otherwise.

Reimplemented from Classifier.

Definition at line 327 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::save ( std::fstream &  file ) const

virtual

This saves the trained FiniteStateMachine model to a file. This overrides the save function in the Classifier base class.

Parameters

file	a reference to the file the FiniteStateMachine model will be saved to

Returns

returns true if the model was saved successfully, false otherwise

Reimplemented from MLBase.

Definition at line 385 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::train_ ( ClassificationData &  trainingData )

virtual

This trains the FiniteStateMachine model, using the labelled classification data. This overrides the train function in the Classifier base class. It converts the data into a TimeSeriesClassificationDataStream format and calls that train_ function.

Parameters

trainingData

a reference to the training data

Returns

returns true if the FiniteStateMachine model was trained, false otherwise

Reimplemented from MLBase.

Definition at line 114 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::train_ ( TimeSeriesClassificationData &  trainingData )

virtual

This trains the FiniteStateMachine model, using the labelled timeseries classification data. This overrides the train function in the Classifier base class. It converts the data into a TimeSeriesClassificationDataStream format and calls that train_ function.

Parameters

trainingData

a reference to the training data

Returns

returns true if the FiniteStateMachine model was trained, false otherwise

Reimplemented from MLBase.

Definition at line 143 of file FiniteStateMachine.cpp.

bool FiniteStateMachine::train_ ( TimeSeriesClassificationDataStream &  data )

virtual

This is the main training function for the FiniteStateMachine model, using the TimeSeriesClassificationDataStream data. This overrides the train function in the Classifier base class.

Parameters

trainingData

a reference to the training data

Returns

returns true if the FiniteStateMachine model was trained, false otherwise

Reimplemented from MLBase.

Definition at line 174 of file FiniteStateMachine.cpp.

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The documentation for this class was generated from the following files:

• FiniteStateMachine.h
• FiniteStateMachine.cpp