Description of the class TBaseModel. More...

#include <TBaseModel.h>

Inheritance diagram for URANIE::XMLProblem::TBaseModel:

Collaboration diagram for URANIE::XMLProblem::TBaseModel:

Public Types
enum	ELanguage { kEMPTY , kC , kCXX , kPMML , kPYTHON , kFORTRAN }

enum	ENorm { kNO , kCR , kMinusOneOne , kZeroOne }

Public Member Functions
	TBaseModel ()

	TBaseModel (TString sinput, TString soutput)

	TBaseModel (TString sname, TString sinput, TString shidden, TString soutput)

virtual	~TBaseModel ()
	Default destructor.

OtherSetting and Getting
void	setName (TString str)

void	setInput (TString str)
	set the \bf "Input" of the model

TString	getInput ()
	get the \bf "Input" of the model

void	setHidden (TString str)
	setHidden

TString	getHidden ()
	getHidden

void	setOutput (TString str)
	set the \bf "Output" of the model

TString	getOutput ()
	getOutput

void	setLanguage (ELanguage val)
	Set the language of the exported code source files.

ELanguage	getLanguage ()
	get the language of the exported code source files

void	setNormalization (ENorm n)
	set the normalisation procedure between [kNO \| kCR \| kMinusOneOne\| kZeroOne]. kCR is the default.

ENorm	getNormalization ()
	Get the normalisation parameter.

void	setFileNameExport (TString str)
	set the file name of the code source file

TString	getFileNameExport ()
	get the file name of the code source file

void	setFunctionNameExport (TString str)
	set the name of the function in the code source file

TString	getFunctionNameExport ()
	get the function name in the code source file

void	setNIteration (Int_t n)
	set the number of iteration (split of the TDs in learning and test data base). 1 is default.

Int_t	getNIteration ()
	get the number of iteration (split of the TDs in learning and test data base)

void	setNInitialization (Int_t n)
	set the number of initialisation step (weights for Neural Network learning). 1 is default value.

Int_t	getNInitialization ()
	get the number of initialisation step (weights for Neural Network learning)

void	setLearn (Double_t dval)
	set the proportion of patterns to split the learning dataset in Learning and test databases. It must be in [0.0, 1.0] and 0.8 is default value.

Double_t	getLearn ()
	get the proportion of patterns to split the learning dataset in Learning and test databases.

void	setTolerance (Double_t dval)
	Set the tolerance parameter. It defined the stoppig rule for the optimization algorithm. It must be possitive and 1.e-4 is default value.

Double_t	getTolerance ()
	Get the tolerance parameter.

void	setSeed (Int_t n)
	set the Seed parameter. It must be positive and 0 is default value.

Int_t	getSeed ()

Init the exported files
void	initExport ()

The Log
void	printLog (Option_t *option="")

Private Attributes
TString	_sinput

TString	_shidden

TString	_soutput

ELanguage	_nlanguage

ENorm	_nNormType

TString	_sfileNameExport
	! The normalized for input and output

TString	_sfunctionNameExport

Int_t	_niteration

Int_t	_ninitialization

Double_t	_dlearn

Double_t	_dtolerance

Int_t	_nseed

Detailed Description

Description of the class TBaseModel.

To be written by the developper.

Member Enumeration Documentation

◆ ELanguage

enum URANIE::XMLProblem::TBaseModel::ELanguage

Enumerator
kEMPTY
kC
kCXX
kPMML
kPYTHON
kFORTRAN

◆ ENorm

enum URANIE::XMLProblem::TBaseModel::ENorm

Enumerator
kNO
kCR
kMinusOneOne
kZeroOne

Constructor & Destructor Documentation

◆ TBaseModel() [1/3]

URANIE::XMLProblem::TBaseModel::TBaseModel ( )

Referenced by ClassImp().

◆ TBaseModel() [2/3]

URANIE::XMLProblem::TBaseModel::TBaseModel	(	TString	sinput,
		TString	soutput
	)

◆ TBaseModel() [3/3]

URANIE::XMLProblem::TBaseModel::TBaseModel	(	TString	sname,
		TString	sinput,
		TString	shidden,
		TString	soutput
	)

◆ ~TBaseModel()

virtual URANIE::XMLProblem::TBaseModel::~TBaseModel ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ getFileNameExport()

TString URANIE::XMLProblem::TBaseModel::getFileNameExport ( )

inline

get the file name of the code source file

Returns: the file name of the code source file

References _sfileNameExport.

◆ getFunctionNameExport()

TString URANIE::XMLProblem::TBaseModel::getFunctionNameExport ( )

inline

get the function name in the code source file

Returns: the function name saved in the code source file

References _sfunctionNameExport.

◆ getHidden()

TString URANIE::XMLProblem::TBaseModel::getHidden ( )

inline

getHidden

Returns: the \bf "Hidden" of the model

References _shidden.

◆ getInput()

TString URANIE::XMLProblem::TBaseModel::getInput ( )

inline

get the \bf "Input" of the model

Returns: the \bf "Input" of the model (attributes names separated by chararcter ":")

References _sinput.

◆ getLanguage()

ELanguage URANIE::XMLProblem::TBaseModel::getLanguage ( )

inline

get the language of the exported code source files

Returns: The language of the exported code source files [kCXX | kPMML | kPYTHON | kFORTRAN]

References _nlanguage.

◆ getLearn()

Double_t URANIE::XMLProblem::TBaseModel::getLearn ( )

inline

get the proportion of patterns to split the learning dataset in Learning and test databases.

Returns: the proportion of patterns

References _dlearn.

◆ getNInitialization()

Int_t URANIE::XMLProblem::TBaseModel::getNInitialization ( )

inline

get the number of initialisation step (weights for Neural Network learning)

Returns: the number of initialisation step (weights for Neural Network learning)

References _ninitialization.

◆ getNIteration()

Int_t URANIE::XMLProblem::TBaseModel::getNIteration ( )

inline

get the number of iteration (split of the TDs in learning and test data base)

Returns: the number of iteration (split of the TDs in learning and test data base)

References _niteration.

◆ getNormalization()

ENorm URANIE::XMLProblem::TBaseModel::getNormalization ( )

inline

Get the normalisation parameter.

get the normalisation

Returns: (ENorm) the normalisation [kCR | kMinusOneOne| kZeroOne].

References _nNormType.

◆ getOutput()

TString URANIE::XMLProblem::TBaseModel::getOutput ( )

inline

getOutput

Returns: the \bf "Output" of the model (attributes names separated by chararcter ":")

References _soutput.

◆ getSeed()

Int_t URANIE::XMLProblem::TBaseModel::getSeed ( )

inline

References _nseed.

◆ getTolerance()

Double_t URANIE::XMLProblem::TBaseModel::getTolerance ( )

inline

Get the tolerance parameter.

Returns

References _dtolerance.

◆ initExport()

void URANIE::XMLProblem::TBaseModel::initExport ( )

Referenced by ClassImp().

◆ printLog()

void URANIE::XMLProblem::TBaseModel::printLog ( Option_t * option = "" )

Referenced by ClassImp().

◆ setFileNameExport()

void URANIE::XMLProblem::TBaseModel::setFileNameExport ( TString str )

inline

set the file name of the code source file

Parameters

str	(TString) the file name of the code source file

References _sfileNameExport.

◆ setFunctionNameExport()

void URANIE::XMLProblem::TBaseModel::setFunctionNameExport ( TString str )

inline

set the name of the function in the code source file

Parameters

str(TString) the name of the function saved in the code source file

References _sfunctionNameExport.

◆ setHidden()

void URANIE::XMLProblem::TBaseModel::setHidden ( TString str )

inline

setHidden

Parameters

str	(TString) the "hidden" of the model (attributes names separated by chararcter ":")

References _shidden.

◆ setInput()

void URANIE::XMLProblem::TBaseModel::setInput ( TString str )

inline

set the \bf "Input" of the model

Parameters

str	(TString) the inputs of the model (attributes names separated by chararcter ":")

References _sinput.

◆ setLanguage()

void URANIE::XMLProblem::TBaseModel::setLanguage ( ELanguage val )

inline

Set the language of the exported code source files.

Parameters

val	(ELanguage) The language of the exported code source files [kCXX \| kPMML \| kPYTHON \| kFORTRAN]

References _nlanguage.

◆ setLearn()

void URANIE::XMLProblem::TBaseModel::setLearn ( Double_t dval )

inline

set the proportion of patterns to split the learning dataset in Learning and test databases. It must be in [0.0, 1.0] and 0.8 is default value.

Parameters

dval	(Double_t) : the proportion of patterns

References _dlearn.

◆ setName()

void URANIE::XMLProblem::TBaseModel::setName ( TString str )

inline

◆ setNInitialization()

void URANIE::XMLProblem::TBaseModel::setNInitialization ( Int_t n )

inline

set the number of initialisation step (weights for Neural Network learning). 1 is default value.

Parameters

n

References _ninitialization.

◆ setNIteration()

void URANIE::XMLProblem::TBaseModel::setNIteration ( Int_t n )

inline

set the number of iteration (split of the TDs in learning and test data base). 1 is default.

Parameters

n	(Int_t) : the number of iteration (split of the TDs in learning and test data base).

References _niteration.

◆ setNormalization()

void URANIE::XMLProblem::TBaseModel::setNormalization ( ENorm n )

inline

set the normalisation procedure between [kNO | kCR | kMinusOneOne| kZeroOne]. kCR is the default.

Parameters

n	(ENorm) the normalisation [kNO \| kCR \| kMinusOneOne\| kZeroOne].

References _nNormType.

◆ setOutput()

void URANIE::XMLProblem::TBaseModel::setOutput ( TString str )

inline

set the \bf "Output" of the model

Parameters

str	(TString) the "outputs" of the model (attributes names separated by chararcter ":")

References _soutput.

◆ setSeed()

void URANIE::XMLProblem::TBaseModel::setSeed ( Int_t n )

inline

set the Seed parameter. It must be positive and 0 is default value.

Parameters

n

References _nseed.

◆ setTolerance()

void URANIE::XMLProblem::TBaseModel::setTolerance ( Double_t dval )

inline

Set the tolerance parameter. It defined the stoppig rule for the optimization algorithm. It must be possitive and 1.e-4 is default value.

Parameters

dval

References _dtolerance.

Member Data Documentation

◆ _dlearn

Double_t URANIE::XMLProblem::TBaseModel::_dlearn

private

Referenced by ClassImp(), getLearn(), and setLearn().

◆ _dtolerance

Double_t URANIE::XMLProblem::TBaseModel::_dtolerance

private

Referenced by ClassImp(), getTolerance(), and setTolerance().

◆ _ninitialization

Int_t URANIE::XMLProblem::TBaseModel::_ninitialization

private

Referenced by ClassImp(), getNInitialization(), and setNInitialization().

◆ _niteration

Int_t URANIE::XMLProblem::TBaseModel::_niteration

private

Referenced by ClassImp(), getNIteration(), and setNIteration().

◆ _nlanguage

ELanguage URANIE::XMLProblem::TBaseModel::_nlanguage

private

Referenced by ClassImp(), getLanguage(), and setLanguage().

◆ _nNormType

ENorm URANIE::XMLProblem::TBaseModel::_nNormType

private

Referenced by ClassImp(), getNormalization(), and setNormalization().

◆ _nseed

Int_t URANIE::XMLProblem::TBaseModel::_nseed

private

Referenced by ClassImp(), getSeed(), and setSeed().

◆ _sfileNameExport

TString URANIE::XMLProblem::TBaseModel::_sfileNameExport

private

! The normalized for input and output

Referenced by ClassImp(), getFileNameExport(), and setFileNameExport().

◆ _sfunctionNameExport

TString URANIE::XMLProblem::TBaseModel::_sfunctionNameExport

private

Referenced by ClassImp(), getFunctionNameExport(), and setFunctionNameExport().

◆ _shidden

TString URANIE::XMLProblem::TBaseModel::_shidden

private

Referenced by ClassImp(), getHidden(), and setHidden().

◆ _sinput

TString URANIE::XMLProblem::TBaseModel::_sinput

private

Referenced by ClassImp(), getInput(), and setInput().

◆ _soutput

TString URANIE::XMLProblem::TBaseModel::_soutput

private

Referenced by ClassImp(), getOutput(), and setOutput().

Documentation / Developer's manual

Available modules

Public Types

Public Member Functions

Private Attributes

Detailed Description

Member Enumeration Documentation

◆ ELanguage

◆ ENorm

Constructor & Destructor Documentation

◆ TBaseModel() [1/3]

◆ TBaseModel() [2/3]

◆ TBaseModel() [3/3]

◆ ~TBaseModel()

Member Function Documentation

◆ getFileNameExport()

◆ getFunctionNameExport()

◆ getHidden()

◆ getInput()

◆ getLanguage()

◆ getLearn()

◆ getNInitialization()

◆ getNIteration()

◆ getNormalization()

◆ getOutput()

◆ getSeed()

◆ getTolerance()

◆ initExport()

◆ printLog()

◆ setFileNameExport()

◆ setFunctionNameExport()

◆ setHidden()

◆ setInput()

◆ setLanguage()

◆ setLearn()

◆ setName()

◆ setNInitialization()

◆ setNIteration()

◆ setNormalization()

◆ setOutput()

◆ setSeed()

◆ setTolerance()

Member Data Documentation

◆ _dlearn

◆ _dtolerance

◆ _ninitialization

◆ _niteration

◆ _nlanguage

◆ _nNormType

◆ _nseed

◆ _sfileNameExport

◆ _sfunctionNameExport

◆ _shidden

◆ _sinput

◆ _soutput