Inheritance diagram for Regressifier:

Public Types
typedef std::map< std::string, Regressifier ()() >	StringRegressifierMap

Public Types inherited from MLBase
enum	BaseType { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER, PRE_PROCSSING, POST_PROCESSING, FEATURE_EXTRACTION, CONTEXT }

Public Member Functions
	Regressifier (const std::string &id="")

virtual	~Regressifier (void)

virtual bool	deepCopyFrom (const Regressifier *regressifier)

bool	copyBaseVariables (const Regressifier *regressifier)

virtual bool	reset () override

virtual bool	clear () override

VectorFloat	getRegressionData () const

Vector< MinMax >	getInputRanges () const

Vector< MinMax >	getOutputRanges () const

Regressifier *	deepCopy () const

const Regressifier &	getBaseRegressifier () const

Regressifier *	create () const

	GRT_DEPRECATED_MSG ("createNewInstance is deprecated, use create() instead.", Regressifier *createNewInstance() const )

	GRT_DEPRECATED_MSG ("createInstanceFromString(id) is deprecated, use create(id) instead.", static Regressifier *createInstanceFromString(const std::string &id))

	GRT_DEPRECATED_MSG ("getRegressifierType is deprecated, use getId() instead", std::string getRegressifierType() 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_ (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_ (TimeSeriesClassificationData &trainingData)

virtual bool	train (ClassificationDataStream 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_ (VectorFloat &inputVector)

virtual bool	predict (MatrixFloat inputMatrix)

virtual bool	predict_ (MatrixFloat &inputMatrix)

virtual bool	map (VectorFloat inputVector)

virtual bool	map_ (VectorFloat &inputVector)

virtual bool	print () const

virtual bool	save (const std::string &filename) const

virtual bool	load (const std::string &filename)

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

virtual bool	load (std::fstream &file)

	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 Vector< std::string >	getRegisteredRegressifiers ()

static Regressifier *	create (const std::string &id)

Static Public Member Functions inherited from GRTBase
static std::string	getGRTVersion (bool returnRevision=true)

static std::string	getGRTRevison ()

Protected Member Functions
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)

Static Protected Member Functions
static StringRegressifierMap *	getMap ()

Protected Attributes
std::string	regressifierType

VectorFloat	regressionData

Vector< MinMax >	inputVectorRanges

Vector< MinMax >	targetVectorRanges

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

Detailed Description

Definition at line 43 of file Regressifier.h.

Member Typedef Documentation

typedef std::map< std::string, Regressifier*(*)() > Regressifier::StringRegressifierMap

Defines a map between a string (which will contain the name of the regressifier, such as LinearRegression) and a function returns a new instance of that regressifier

Definition at line 113 of file Regressifier.h.

Constructor & Destructor Documentation

Regressifier::Regressifier ( const std::string & id = "" )

Default Regressifier Destructor

Parameters

id	a unique string that identifies the Regressifier parent class (e.g., LinearRegression)

Definition at line 60 of file Regressifier.cpp.

Regressifier::~Regressifier ( void )

virtual

Default Regressifier Destructor

Definition at line 66 of file Regressifier.cpp.

Member Function Documentation

bool Regressifier::clear ( )

overridevirtual

This function clears the regressifier 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 MLBase.

Reimplemented in MLP, and RegressionTree.

Definition at line 111 of file Regressifier.cpp.

bool Regressifier::copyBaseVariables ( const Regressifier * regressifier )

This copies the Regressifier variables from the regressifier pointer to this instance.

Parameters

regressifier a pointer to a regressifier from which the values will be copied to this instance

Returns: returns true if the copy was successfull, false otherwise

Definition at line 84 of file Regressifier.cpp.

Regressifier * Regressifier::create ( const std::string & id )

static

Creates a new regressifier instance based on the input string (which should contain the name of a valid regressifier such as LinearRegression).

Parameters

id	the id of the regressifier

Returns: a pointer to the new instance of the regressifier

Definition at line 34 of file Regressifier.cpp.

Regressifier * Regressifier::create ( ) const

Creates a new regressifier instance based on the current regressifierType string value.

Returns: Regressifier*: a pointer to the new instance of the regressifier

Definition at line 43 of file Regressifier.cpp.

Regressifier * Regressifier::deepCopy ( ) const

This creates a new Regressifier instance and deep copies the variables and models from this instance into the deep copy. The function will then return a pointer to the new instance. It is up to the user who calls this function to delete the dynamic instance when they are finished using it.

Returns: returns a pointer to a new Regressifier instance which is a deep copy of this instance

Definition at line 47 of file Regressifier.cpp.

virtual bool Regressifier::deepCopyFrom ( const Regressifier * regressifier )

inlinevirtual

This is the base deep copy function for the Regressifier modules. This function should be overwritten by the derived class. This deep copies the variables and models from the regressifier pointer to this regressifier instance.

Parameters

regressifier a pointer to the Regressifier base class, this should be pointing to another instance of a matching derived class

Returns: returns true if the deep copy was successfull, false otherwise (the Regressifier base class will always return false)

Reimplemented in MultidimensionalRegression, RegressionTree, LogisticRegression, MLP, and LinearRegression.

Definition at line 64 of file Regressifier.h.

const Regressifier & Regressifier::getBaseRegressifier ( ) const

Returns a pointer to this regressifier. This is useful for a derived class so it can get easy access to this base regressifier.

Returns: a reference to this regressifier

Definition at line 139 of file Regressifier.cpp.

Vector< MinMax > Regressifier::getInputRanges ( ) const

Returns the ranges of the input (i.e. feature) data.

Returns: returns a Vector of MinMax values representing the ranges of the input data

Definition at line 131 of file Regressifier.cpp.

Vector< MinMax > Regressifier::getOutputRanges ( ) const

Returns the ranges of the output (i.e. target) data.

Returns: returns a Vector of MinMax values representing the ranges of the target data

Definition at line 135 of file Regressifier.cpp.

Vector< std::string > Regressifier::getRegisteredRegressifiers ( )

static

Returns a Vector of the names of all regressifiers that have been registered with the base regressifier.

Returns: a Vector containing the names of the regressifiers that have been registered with the base regressifier

Definition at line 73 of file Regressifier.cpp.

VectorFloat Regressifier::getRegressionData ( ) const

Gets a Vector containing the regression data output by the regression algorithm, this will be an M-dimensional Vector, where M is the number of output dimensions in the model.

Returns: returns a Vector containing the regression data output by the regression algorithm, an empty Vector will be returned if the model has not been trained

Definition at line 124 of file Regressifier.cpp.

bool Regressifier::loadBaseSettingsFromFile ( std::fstream & file )

protected

Loads the core base settings from a file.

Returns: returns true if the base settings were loaded, false otherwise

Definition at line 168 of file Regressifier.cpp.

bool Regressifier::reset ( )

overridevirtual

This resets the regressifier. This overrides the reset function in the MLBase base class.

Returns: returns true if the regressifier was reset, false otherwise

Reimplemented from MLBase.

Definition at line 103 of file Regressifier.cpp.

bool Regressifier::saveBaseSettingsToFile ( std::fstream & file ) const

protected

Saves the core base settings to a file.

Returns: returns true if the base settings were saved, false otherwise

Definition at line 143 of file Regressifier.cpp.

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

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation