Definition at line 77 of file Factory.h.

Public Types
typedef std::vector< IMethod * >	MVector

Public Types inherited from TObject
enum	EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) }

enum	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }

Public Member Functions
	Factory (TString theJobName, TFile *theTargetFile, TString theOption="")

virtual	~Factory ()
	destructor delete fATreeEvent; More...

virtual const char *	GetName () const
	Returns name of object. More...

void	AddSignalTrainingEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event More...

void	AddBackgroundTrainingEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event More...

void	AddSignalTestEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal testing event More...

void	AddBackgroundTestEvent (const std::vector< Double_t > &event, Double_t weight=1.0)
	add signal training event More...

void	AddTrainingEvent (const TString &className, const std::vector< Double_t > &event, Double_t weight)
	add signal training event More...

void	AddTestEvent (const TString &className, const std::vector< Double_t > &event, Double_t weight)
	add signal test event More...

void	AddEvent (const TString &className, Types::ETreeType tt, const std::vector< Double_t > &event, Double_t weight)
	add event vector event : the order of values is: variables + targets + spectators More...

Bool_t	UserAssignEvents (UInt_t clIndex)

TTree *	CreateEventAssignTrees (const TString &name)
	create the data assignment tree (for event-wise data assignment by user) More...

DataSetInfo &	AddDataSet (DataSetInfo &)

DataSetInfo &	AddDataSet (const TString &)

void	SetInputTrees (const TString &signalFileName, const TString &backgroundFileName, Double_t signalWeight=1.0, Double_t backgroundWeight=1.0)

void	SetInputTrees (TTree *inputTree, const TCut &SigCut, const TCut &BgCut)
	define the input trees for signal and background from single input tree, containing both signal and background events distinguished by the type identifiers: SigCut and BgCut More...

void	SetInputTrees (TTree signal, TTree background, Double_t signalWeight=1.0, Double_t backgroundWeight=1.0)
	define the input trees for signal and background; no cuts are applied More...

void	AddSignalTree (TTree *signal, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	number of signal events (used to compute significance) More...

void	AddSignalTree (TString datFileS, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	add signal tree from text file More...

void	AddSignalTree (TTree *signal, Double_t weight, const TString &treetype)

void	SetSignalTree (TTree *signal, Double_t weight=1.0)

void	AddBackgroundTree (TTree *background, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	number of signal events (used to compute significance) More...

void	AddBackgroundTree (TString datFileB, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)
	add background tree from text file More...

void	AddBackgroundTree (TTree *background, Double_t weight, const TString &treetype)

void	SetBackgroundTree (TTree *background, Double_t weight=1.0)

void	SetSignalWeightExpression (const TString &variable)

void	SetBackgroundWeightExpression (const TString &variable)

void	AddRegressionTree (TTree *tree, Double_t weight=1.0, Types::ETreeType treetype=Types::kMaxTreeType)

void	SetTree (TTree *tree, const TString &className, Double_t weight)
	set background tree More...

void	AddTree (TTree *tree, const TString &className, Double_t weight=1.0, const TCut &cut="", Types::ETreeType tt=Types::kMaxTreeType)

void	AddTree (TTree *tree, const TString &className, Double_t weight, const TCut &cut, const TString &treeType)
	number of signal events (used to compute significance) More...

void	SetInputVariables (std::vector< TString > *theVariables)
	fill input variables in data set More...

void	AddVariable (const TString &expression, const TString &title, const TString &unit, char type='F', Double_t min=0, Double_t max=0)
	user inserts discriminating variable in data set info More...

void	AddVariable (const TString &expression, char type='F', Double_t min=0, Double_t max=0)
	user inserts discriminating variable in data set info More...

void	AddTarget (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)
	user inserts target in data set info More...

void	AddRegressionTarget (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)

void	AddSpectator (const TString &expression, const TString &title="", const TString &unit="", Double_t min=0, Double_t max=0)
	user inserts target in data set info More...

void	SetWeightExpression (const TString &variable, const TString &className="")
	Log() << kWarning << DefaultDataSetInfo().GetNClasses() /fClasses.size()/ << Endl;. More...

void	SetCut (const TString &cut, const TString &className="")

void	SetCut (const TCut &cut, const TString &className="")

void	AddCut (const TString &cut, const TString &className="")

void	AddCut (const TCut &cut, const TString &className="")

void	PrepareTrainingAndTestTree (const TCut &cut, const TString &splitOpt)
	prepare the training and test trees -> same cuts for signal and background More...

void	PrepareTrainingAndTestTree (TCut sigcut, TCut bkgcut, const TString &splitOpt)
	prepare the training and test trees More...

void	PrepareTrainingAndTestTree (const TCut &cut, Int_t Ntrain, Int_t Ntest=-1)
	prepare the training and test trees kept for backward compatibility More...

void	PrepareTrainingAndTestTree (const TCut &cut, Int_t NsigTrain, Int_t NbkgTrain, Int_t NsigTest, Int_t NbkgTest, const TString &otherOpt="SplitMode=Random:!V")
	prepare the training and test trees More...

MethodBase *	BookMethod (TString theMethodName, TString methodTitle, TString theOption="")
	Book a classifier or regression method. More...

MethodBase *	BookMethod (Types::EMVA theMethod, TString methodTitle, TString theOption="")
	books MVA method; the option configuration string is custom for each MVA the TString field "theNameAppendix" serves to define (and distinguish) several instances of a given MVA, eg, when one wants to compare the performance of various configurations More...

MethodBase *	BookMethod (TMVA::Types::EMVA, TString, TString, TMVA::Types::EMVA, TString)

void	OptimizeAllMethods (TString fomType="ROCIntegral", TString fitType="FitGA")
	iterates through all booked methods and sees if they use parameter tuning and if so. More...

void	OptimizeAllMethodsForClassification (TString fomType="ROCIntegral", TString fitType="FitGA")

void	OptimizeAllMethodsForRegression (TString fomType="ROCIntegral", TString fitType="FitGA")

void	TrainAllMethods ()
	iterates through all booked methods and calls training More...

void	TrainAllMethodsForClassification (void)

void	TrainAllMethodsForRegression (void)

void	TestAllMethods ()

void	EvaluateAllMethods (void)
	iterates over all MVAs that have been booked, and calls their evaluation methods More...

void	EvaluateAllVariables (TString options="")
	iterates over all MVA input varables and evaluates them More...

void	DeleteAllMethods (void)
	delete methods More...

IMethod *	GetMethod (const TString &title) const
	returns pointer to MVA that corresponds to given method title More...

Bool_t	Verbose (void) const

void	SetVerbose (Bool_t v=kTRUE)

virtual void	MakeClass (const TString &methodTitle="") const
	Print predefined help message of classifier iterate over methods and test. More...

void	PrintHelpMessage (const TString &methodTitle="") const
	Print predefined help message of classifier iterate over methods and test. More...

Public Member Functions inherited from TMVA::Configurable
	Configurable (const TString &theOption="")

virtual	~Configurable ()
	default destructur More...

virtual void	ParseOptions ()
	options parser More...

void	PrintOptions () const
	prints out the options set in the options string and the defaults More...

const char *	GetConfigName () const

const char *	GetConfigDescription () const

void	SetConfigName (const char *n)

void	SetConfigDescription (const char *d)

template<class T >
OptionBase *	DeclareOptionRef (T &ref, const TString &name, const TString &desc="")

template<class T >
OptionBase *	DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")

template<class T >
void	AddPreDefVal (const T &)

template<class T >
void	AddPreDefVal (const TString &optname, const T &)

void	CheckForUnusedOptions () const
	checks for unused options in option string More...

const TString &	GetOptions () const

void	SetOptions (const TString &s)

void	WriteOptionsToStream (std::ostream &o, const TString &prefix) const
	write options to output stream (e.g. in writing the MVA weight files More...

void	ReadOptionsFromStream (std::istream &istr)
	read option back from the weight file More...

void	AddOptionsXMLTo (void *parent) const
	write options to XML file More...

void	ReadOptionsFromXML (void *node)

void	SetMsgType (EMsgType t)

template<class T >
TMVA::OptionBase *	DeclareOptionRef (T &ref, const TString &name, const TString &desc)

template<class T >
TMVA::OptionBase *	DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)

Public Member Functions inherited from TObject
	TObject ()

	TObject (const TObject &object)
	TObject copy ctor. More...

TObject &	operator= (const TObject &rhs)
	TObject assignment operator. More...

virtual	~TObject ()
	TObject destructor. More...

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad. More...

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action. More...

virtual const char *	ClassName () const
	Returns name of class to which the object belongs. More...

virtual void	Clear (Option_t *="")

virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility. More...

virtual Int_t	Compare (const TObject *obj) const
	Compare abstract method. More...

virtual void	Copy (TObject &object) const
	Copy this to obj. More...

virtual void	Delete (Option_t *option="")
	Delete this object. More...

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object. More...

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects. More...

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs. More...

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current pad. More...

virtual void	Dump () const
	Dump contents of object on stdout. More...

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g. More...

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray. More...

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py). More...

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes. More...

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes. More...

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object. More...

virtual UInt_t	GetUniqueID () const
	Return the unique object id. More...

virtual const char *	GetIconName () const
	Returns mime type name of object. More...

virtual Option_t *	GetOption () const

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py). More...

virtual const char *	GetTitle () const
	Returns title of object. More...

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out. More...

virtual ULong_t	Hash () const
	Return hash value for this object. More...

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname". More...

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl. More...

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas. More...

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory). More...

virtual Bool_t	IsSortable () const

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification. More...

virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout. More...

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself. More...

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list. More...

virtual void	Print (Option_t *option="") const
	This method must be overridden when a class wants to print itself. More...

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory. More...

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list. More...

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename. More...

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out". More...

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object. More...

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id. More...

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory. More...

void *	operator new (size_t sz)

void *	operator new[] (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz, void *vp)

void	operator delete (void *ptr)
	Operator delete. More...

void	operator delete[] (void *ptr)
	Operator delete []. More...

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f. More...

void	SetBit (UInt_t f)

void	ResetBit (UInt_t f)

Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

void	InvertBit (UInt_t f)

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message. More...

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message. More...

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message. More...

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message. More...

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message. More...

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete. More...

Static Public Member Functions
static TDirectory *	RootBaseDir ()

Static Public Member Functions inherited from TObject
static Long_t	GetDtorOnly ()
	Return destructor only flag. More...

static void	SetDtorOnly (void *obj)
	Set destructor only flag. More...

static Bool_t	GetObjectStat ()
	Get status of object stat flag. More...

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable. More...

Private Types
enum	DataAssignType { kUndefined = 0, kAssignTrees, kAssignEvents }
	jobname, used as extension in weight file names More...

Private Member Functions
void	Greetings ()
	print welcome message options are: kLogoWelcomeMsg, kIsometricWelcomeMsg, kLeanWelcomeMsg More...

void	WriteDataInformation ()
	put correlations of input data and a few (default + user selected) transformations into the root file More...

DataInputHandler &	DataInput ()

DataSetInfo &	DefaultDataSetInfo ()
	default creation More...

void	SetInputTreesFromEventAssignTrees ()
	assign event-wise local trees to data set More...

Private Attributes
DataSetManager *	fDataSetManager

DataInputHandler *	fDataInputHandler
	ROOT output file. More...

std::vector< TMVA::VariableTransformBase * >	fDefaultTrfs

TString	fOptions
	list of transformations on default DataSet More...

TString	fTransformations
	option string given by construction (presently only "V") More...

Bool_t	fVerbose
	List of transformations to test. More...

MVector	fMethods
	verbose mode More...

TString	fJobName
	all MVA methods More...

DataAssignType	fDataAssignType

std::vector< TTree * >	fTrainAssignTree
	flags for data assigning More...

std::vector< TTree * >	fTestAssignTree
	for each class: tmp tree if user wants to assign the events directly More...

Int_t	fATreeType
	for each class: tmp tree if user wants to assign the events directly More...

Float_t	fATreeWeight

Float_t *	fATreeEvent

Types::EAnalysisType	fAnalysisType

Static Private Attributes
static TFile *	fgTargetFile = 0

Additional Inherited Members
Protected Member Functions inherited from TMVA::Configurable
Bool_t	LooseOptionCheckingEnabled () const

void	EnableLooseOptions (Bool_t b=kTRUE)

void	WriteOptionsReferenceToFile ()
	write complete options to output stream More...

void	ResetSetFlag ()
	resets the IsSet falg for all declare options to be called before options are read from stream More...

const TString &	GetReferenceFile () const

MsgLogger &	Log () const

Protected Member Functions inherited from TObject
void	MakeZombie ()

virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected). More...

#include <TMVA/Factory.h>

Inheritance diagram for TMVA::Factory:

Collaboration diagram for TMVA::Factory:

Member Typedef Documentation

typedef std::vector<IMethod*> TMVA::Factory::MVector

Definition at line 80 of file Factory.h.

Member Enumeration Documentation

enum TMVA::Factory::DataAssignType

private

jobname, used as extension in weight file names

Enumerator
kUndefined
kAssignTrees
kAssignEvents

Definition at line 264 of file Factory.h.

Constructor & Destructor Documentation

TMVA::Factory::Factory	(	TString	theJobName,
		TFile *	theTargetFile,
		TString	theOption = `""`
	)

TMVA::Factory::~Factory ( void )

virtual

destructor delete fATreeEvent;

Definition at line 182 of file Factory.cxx.

Member Function Documentation

void TMVA::Factory::AddBackgroundTestEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 302 of file Factory.cxx.

void TMVA::Factory::AddBackgroundTrainingEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 294 of file Factory.cxx.

void TMVA::Factory::AddBackgroundTree	(	TTree *	background,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

number of signal events (used to compute significance)

Definition at line 452 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::AddBackgroundTree	(	TString	datFileB,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

add background tree from text file

Definition at line 459 of file Factory.cxx.

void TMVA::Factory::AddBackgroundTree	(	TTree *	background,
		Double_t	weight,
		const TString &	treetype
	)

Definition at line 474 of file Factory.cxx.

void TMVA::Factory::AddCut	(	const TString &	cut,
		const TString &	className = `""`
	)

Definition at line 628 of file Factory.cxx.

void TMVA::Factory::AddCut	(	const TCut &	cut,
		const TString &	className = `""`
	)

Definition at line 635 of file Factory.cxx.

TMVA::DataSetInfo & TMVA::Factory::AddDataSet ( DataSetInfo & dsi )

Definition at line 223 of file Factory.cxx.

TMVA::DataSetInfo & TMVA::Factory::AddDataSet ( const TString & dsiName )

Definition at line 230 of file Factory.cxx.

void TMVA::Factory::AddEvent	(	const TString &	className,
		Types::ETreeType	tt,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add event vector event : the order of values is: variables + targets + spectators

Definition at line 327 of file Factory.cxx.

void TMVA::Factory::AddRegressionTarget	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

inline

Definition at line 154 of file Factory.h.

void TMVA::Factory::AddRegressionTree	(	TTree *	tree,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

inline

Definition at line 132 of file Factory.h.

void TMVA::Factory::AddSignalTestEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal testing event

Definition at line 286 of file Factory.cxx.

void TMVA::Factory::AddSignalTrainingEvent	(	const std::vector< Double_t > &	event,
		Double_t	weight = `1.0`
	)

add signal training event

Definition at line 278 of file Factory.cxx.

void TMVA::Factory::AddSignalTree	(	TTree *	signal,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

number of signal events (used to compute significance)

Definition at line 421 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::AddSignalTree	(	TString	datFileS,
		Double_t	weight = `1.0`,
		Types::ETreeType	treetype = `Types::kMaxTreeType`
	)

add signal tree from text file

Definition at line 429 of file Factory.cxx.

void TMVA::Factory::AddSignalTree	(	TTree *	signal,
		Double_t	weight,
		const TString &	treetype
	)

Definition at line 444 of file Factory.cxx.

void TMVA::Factory::AddSpectator	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts target in data set info

Definition at line 564 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::AddTarget	(	const TString &	expression,
		const TString &	title = `""`,
		const TString &	unit = `""`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts target in data set info

Definition at line 552 of file Factory.cxx.

Referenced by AddRegressionTarget().

void TMVA::Factory::AddTestEvent	(	const TString &	className,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add signal test event

Definition at line 318 of file Factory.cxx.

void TMVA::Factory::AddTrainingEvent	(	const TString &	className,
		const std::vector< Double_t > &	event,
		Double_t	weight
	)

add signal training event

Definition at line 310 of file Factory.cxx.

void TMVA::Factory::AddTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight = `1.0`,
		const TCut &	cut = `""`,
		Types::ETreeType	tt = `Types::kMaxTreeType`
	)

Definition at line 401 of file Factory.cxx.

Referenced by AddRegressionTree().

void TMVA::Factory::AddTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight,
		const TCut &	cut,
		const TString &	treeType
	)

number of signal events (used to compute significance)

Definition at line 384 of file Factory.cxx.

void TMVA::Factory::AddVariable	(	const TString &	expression,
		const TString &	title,
		const TString &	unit,
		char	type = `'F'`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts discriminating variable in data set info

Definition at line 534 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::AddVariable	(	const TString &	expression,
		char	type = `'F'`,
		Double_t	min = `0`,
		Double_t	max = `0`
	)

user inserts discriminating variable in data set info

Definition at line 543 of file Factory.cxx.

TMVA::MethodBase * TMVA::Factory::BookMethod	(	TString	theMethodName,
		TString	methodTitle,
		TString	theOption = `""`
	)

Book a classifier or regression method.

Definition at line 700 of file Factory.cxx.

Referenced by Classification().

TMVA::MethodBase * TMVA::Factory::BookMethod	(	Types::EMVA	theMethod,
		TString	methodTitle,
		TString	theOption = `""`
	)

books MVA method; the option configuration string is custom for each MVA the TString field "theNameAppendix" serves to define (and distinguish) several instances of a given MVA, eg, when one wants to compare the performance of various configurations

Definition at line 807 of file Factory.cxx.

MethodBase* TMVA::Factory::BookMethod	(	TMVA::Types::EMVA	,
		TString	,
		TString	,
		TMVA::Types::EMVA	,
		TString
	)

inline

Definition at line 184 of file Factory.h.

TTree * TMVA::Factory::CreateEventAssignTrees ( const TString & name )

create the data assignment tree (for event-wise data assignment by user)

Definition at line 245 of file Factory.cxx.

DataInputHandler& TMVA::Factory::DataInput ( )

inlineprivate

Definition at line 237 of file Factory.h.

TMVA::DataSetInfo & TMVA::Factory::DefaultDataSetInfo ( )

private

default creation

Definition at line 573 of file Factory.cxx.

void TMVA::Factory::DeleteAllMethods ( void )

delete methods

Definition at line 204 of file Factory.cxx.

void TMVA::Factory::EvaluateAllMethods ( void )

iterates over all MVAs that have been booked, and calls their evaluation methods

Definition at line 1179 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::EvaluateAllVariables ( TString options = "" )

iterates over all MVA input varables and evaluates them

Definition at line 1164 of file Factory.cxx.

TMVA::IMethod * TMVA::Factory::GetMethod ( const TString & title ) const

returns pointer to MVA that corresponds to given method title

Definition at line 815 of file Factory.cxx.

virtual const char* TMVA::Factory::GetName ( ) const

inlinevirtual

Returns name of object.

This default method returns the class name. Classes that give objects a name should override this method.

Reimplemented from TMVA::Configurable.

Definition at line 88 of file Factory.h.

void TMVA::Factory::Greetings ( )

private

print welcome message options are: kLogoWelcomeMsg, kIsometricWelcomeMsg, kLeanWelcomeMsg

Definition at line 171 of file Factory.cxx.

void TMVA::Factory::MakeClass ( const TString & methodTitle = "" ) const

virtual

Print predefined help message of classifier iterate over methods and test.

Definition at line 1109 of file Factory.cxx.

void TMVA::Factory::OptimizeAllMethods	(	TString	fomType = `"ROCIntegral"`,
		TString	fitType = `"FitGA"`
	)

iterates through all booked methods and sees if they use parameter tuning and if so.

does just that i.e. calls "Method::Train()" for different parameter setttings and keeps in mind the "optimal one"... and that's the one that will later on be used in the main training loop.

Definition at line 925 of file Factory.cxx.

Referenced by OptimizeAllMethodsForClassification(), and OptimizeAllMethodsForRegression().

void TMVA::Factory::OptimizeAllMethodsForClassification	(	TString	fomType = `"ROCIntegral"`,
		TString	fitType = `"FitGA"`
	)

inline

Definition at line 192 of file Factory.h.

void TMVA::Factory::OptimizeAllMethodsForRegression	(	TString	fomType = `"ROCIntegral"`,
		TString	fitType = `"FitGA"`
	)

inline

Definition at line 193 of file Factory.h.

void TMVA::Factory::PrepareTrainingAndTestTree	(	const TCut &	cut,
		const TString &	splitOpt
	)

prepare the training and test trees -> same cuts for signal and background

Definition at line 673 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::PrepareTrainingAndTestTree	(	TCut	sigcut,
		TCut	bkgcut,
		const TString &	splitOpt
	)

prepare the training and test trees

Definition at line 685 of file Factory.cxx.

void TMVA::Factory::PrepareTrainingAndTestTree	(	const TCut &	cut,
		Int_t	Ntrain,
		Int_t	Ntest = `-1`
	)

prepare the training and test trees kept for backward compatibility

Definition at line 659 of file Factory.cxx.

void TMVA::Factory::PrepareTrainingAndTestTree	(	const TCut &	cut,
		Int_t	NsigTrain,
		Int_t	NbkgTrain,
		Int_t	NsigTest,
		Int_t	NbkgTest,
		const TString &	otherOpt = `"SplitMode=Random:!V"`
	)

prepare the training and test trees

Definition at line 643 of file Factory.cxx.

void TMVA::Factory::PrintHelpMessage ( const TString & methodTitle = "" ) const

Print predefined help message of classifier iterate over methods and test.

Definition at line 1137 of file Factory.cxx.

static TDirectory* TMVA::Factory::RootBaseDir ( )

inlinestatic

Definition at line 228 of file Factory.h.

Referenced by TMVA::RuleFit::MakeVisHists(), and TMVA::MethodBase::MethodBaseDir().

void TMVA::Factory::SetBackgroundTree	(	TTree *	background,
		Double_t	weight = `1.0`
	)

Definition at line 488 of file Factory.cxx.

void TMVA::Factory::SetBackgroundWeightExpression ( const TString & variable )

Definition at line 596 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::SetCut	(	const TString &	cut,
		const TString &	className = `""`
	)

Definition at line 615 of file Factory.cxx.

void TMVA::Factory::SetCut	(	const TCut &	cut,
		const TString &	className = `""`
	)

Definition at line 621 of file Factory.cxx.

void TMVA::Factory::SetInputTrees	(	const TString &	signalFileName,
		const TString &	backgroundFileName,
		Double_t	signalWeight = `1.0`,
		Double_t	backgroundWeight = `1.0`
	)

Definition at line 513 of file Factory.cxx.

void TMVA::Factory::SetInputTrees	(	TTree *	inputTree,
		const TCut &	SigCut,
		const TCut &	BgCut
	)

define the input trees for signal and background from single input tree, containing both signal and background events distinguished by the type identifiers: SigCut and BgCut

Definition at line 525 of file Factory.cxx.

void TMVA::Factory::SetInputTrees	(	TTree *	signal,
		TTree *	background,
		Double_t	signalWeight = `1.0`,
		Double_t	backgroundWeight = `1.0`
	)

define the input trees for signal and background; no cuts are applied

Definition at line 504 of file Factory.cxx.

void TMVA::Factory::SetInputTreesFromEventAssignTrees ( )

private

assign event-wise local trees to data set

Definition at line 369 of file Factory.cxx.

void TMVA::Factory::SetInputVariables ( std::vector< TString > * theVariables )

fill input variables in data set

Definition at line 581 of file Factory.cxx.

void TMVA::Factory::SetSignalTree	(	TTree *	signal,
		Double_t	weight = `1.0`
	)

Definition at line 481 of file Factory.cxx.

void TMVA::Factory::SetSignalWeightExpression ( const TString & variable )

Definition at line 589 of file Factory.cxx.

void TMVA::Factory::SetTree	(	TTree *	tree,
		const TString &	className,
		Double_t	weight
	)

set background tree

Definition at line 496 of file Factory.cxx.

void TMVA::Factory::SetVerbose ( Bool_t v = kTRUE )

Definition at line 216 of file Factory.cxx.

void TMVA::Factory::SetWeightExpression	(	const TString &	variable,
		const TString &	className = `""`
	)

Log() << kWarning << DefaultDataSetInfo().GetNClasses() /*fClasses.size()*/ << Endl;.

Definition at line 604 of file Factory.cxx.

void TMVA::Factory::TestAllMethods ( )

Definition at line 1079 of file Factory.cxx.

Referenced by Classification().

void TMVA::Factory::TrainAllMethods ( )

iterates through all booked methods and calls training

Definition at line 959 of file Factory.cxx.

Referenced by Classification(), TrainAllMethodsForClassification(), and TrainAllMethodsForRegression().

void TMVA::Factory::TrainAllMethodsForClassification ( void )

inline

Definition at line 197 of file Factory.h.

void TMVA::Factory::TrainAllMethodsForRegression ( void )

inline

Definition at line 198 of file Factory.h.

Bool_t TMVA::Factory::UserAssignEvents ( UInt_t clIndex )

Definition at line 361 of file Factory.cxx.

Bool_t TMVA::Factory::Verbose ( void ) const

inline

Definition at line 213 of file Factory.h.

void TMVA::Factory::WriteDataInformation ( )

private

put correlations of input data and a few (default + user selected) transformations into the root file

Definition at line 831 of file Factory.cxx.

Member Data Documentation

Types::EAnalysisType TMVA::Factory::fAnalysisType

private

Definition at line 275 of file Factory.h.

Float_t* TMVA::Factory::fATreeEvent

private

Definition at line 273 of file Factory.h.

Int_t TMVA::Factory::fATreeType

private

for each class: tmp tree if user wants to assign the events directly

Definition at line 271 of file Factory.h.

Float_t TMVA::Factory::fATreeWeight

private

Definition at line 272 of file Factory.h.

DataAssignType TMVA::Factory::fDataAssignType

private

Definition at line 267 of file Factory.h.

DataInputHandler* TMVA::Factory::fDataInputHandler

private

ROOT output file.

Definition at line 251 of file Factory.h.

Referenced by DataInput().

DataSetManager* TMVA::Factory::fDataSetManager

private

Definition at line 247 of file Factory.h.

std::vector<TMVA::VariableTransformBase*> TMVA::Factory::fDefaultTrfs

private

Definition at line 253 of file Factory.h.

TFile * TMVA::Factory::fgTargetFile = 0

staticprivate

Definition at line 249 of file Factory.h.

Referenced by RootBaseDir().

TString TMVA::Factory::fJobName

private

all MVA methods

Definition at line 261 of file Factory.h.

MVector TMVA::Factory::fMethods

private

verbose mode

Definition at line 260 of file Factory.h.

TString TMVA::Factory::fOptions

private

list of transformations on default DataSet

Definition at line 256 of file Factory.h.

std::vector<TTree*> TMVA::Factory::fTestAssignTree

private

for each class: tmp tree if user wants to assign the events directly

Definition at line 269 of file Factory.h.

std::vector<TTree*> TMVA::Factory::fTrainAssignTree

private

flags for data assigning

Definition at line 268 of file Factory.h.

TString TMVA::Factory::fTransformations

private

option string given by construction (presently only "V")

Definition at line 257 of file Factory.h.

Bool_t TMVA::Factory::fVerbose

private

List of transformations to test.

Definition at line 258 of file Factory.h.

Referenced by Verbose().

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

tmva/tmva/inc/TMVA/Factory.h
tmva/tmva/src/Factory.cxx

Public Types

Public Member Functions

Static Public Member Functions

Private Types

Private Member Functions

Private Attributes

Static Private Attributes

Additional Inherited Members

Member Typedef Documentation

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation