Definition at line 163 of file Classification.h.

Public Member Functions
	Classification (DataLoader loader, TFile file, TString options)
	Contructor to create a two class classifier.

	Classification (DataLoader *loader, TString options)
	Contructor to create a two class classifier without output file.

	~Classification ()

virtual void	Evaluate ()
	Method to perform Train/Test over all ml method booked.

MethodBase *	GetMethod (TString methodname, TString methodtitle)
	Return a TMVA::MethodBase object.

std::vector< ClassificationResult > &	GetResults ()
	return the the vector of TMVA::Experimental::ClassificationResult objects.

virtual void	Test ()
	Perform test evaluation in all booked methods.

virtual void	TestMethod (TString methodname, TString methodtitle)
	Lets perform test an specific ml method.

virtual void	TestMethod (Types::EMVA method, TString methodtitle)
	Lets perform test an specific ml method given the method type in enum TMVA::Types::EMVA.

virtual void	Train ()
	Method to train all booked ml methods.

virtual void	TrainMethod (TString methodname, TString methodtitle)
	Lets train an specific ml method.

virtual void	TrainMethod (Types::EMVA method, TString methodtitle)
	Lets train an specific ml method given the method type in enum TMVA::Types::EMVA.

Public Member Functions inherited from TMVA::Envelope
	~Envelope ()
	Default destructor.

virtual void	BookMethod (TString methodname, TString methodtitle, TString options="")
	Method to book the machine learning method to perform the algorithm.

virtual void	BookMethod (Types::EMVA method, TString methodtitle, TString options="")
	Method to book the machine learning method to perform the algorithm.

DataLoader *	GetDataLoader ()
	Method to get the pointer to TMVA::DataLoader object.

TFile *	GetFile ()
	Method to get the pointer to TFile object.

std::vector< OptionMap > &	GetMethods ()
	Method get the Booked methods in a option map object.

Bool_t	HasMethod (TString methodname, TString methodtitle)
	function to check methods booked

Bool_t	IsModelPersistence ()
	Method to see if the algorithm model is saved in xml or serialized files.

Bool_t	IsSilentFile ()
	Method to see if a file is available to save results.

Bool_t	IsVerbose ()
	Method to see if the algorithm should print extra information.

virtual void	ParseOptions ()
	Method to parse the internal option string.

void	SetDataLoader (DataLoader *dalaloader)
	Method to set the pointer to TMVA::DataLoader object.

void	SetFile (TFile *file)
	Method to set the pointer to TFile object, with a writable file.

void	SetModelPersistence (Bool_t status=kTRUE)
	Method enable model persistence, then algorithms model is saved in xml or serialized files.

void	SetVerbose (Bool_t status)
	Method enable print extra information in the algorithms.

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

virtual	~Configurable ()
	default destructor

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

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

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

template<class T >
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)

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

const char *	GetConfigDescription () const

const char *	GetConfigName () const

const TString &	GetOptions () const

MsgLogger &	Log () const

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

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

void	ReadOptionsFromXML (void *node)

void	SetConfigDescription (const char *d)

void	SetConfigName (const char *n)

void	SetMsgType (EMsgType t)

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

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

	TNamed (const TNamed &named)
	TNamed copy ctor.

	TNamed (const TString &name, const TString &title)

virtual	~TNamed ()
	TNamed destructor.

virtual void	Clear (Option_t *option="")
	Set name and title to empty strings ("").

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

virtual Int_t	Compare (const TObject *obj) const
	Compare two TNamed objects.

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

virtual void	FillBuffer (char *&buffer)
	Encode TNamed into output buffer.

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

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

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

virtual Bool_t	IsSortable () const

virtual void	ls (Option_t *option="") const
	List TNamed name and title.

TNamed &	operator= (const TNamed &rhs)
	TNamed assignment operator.

virtual void	Print (Option_t *option="") const
	Print TNamed name and title.

virtual void	SetName (const char *name)
	Set the name of the TNamed.

virtual void	SetNameTitle (const char name, const char title)
	Set all the TNamed parameters (name and title).

virtual void	SetTitle (const char *title="")
	Set the title of the TNamed.

virtual Int_t	Sizeof () const
	Return size of the TNamed part of the TObject.

Public Member Functions inherited from TObject
	TObject ()
	TObject constructor.

	TObject (const TObject &object)
	TObject copy ctor.

virtual	~TObject ()
	TObject destructor.

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

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

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

ULong_t	CheckedHash ()
	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.

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

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

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

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

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

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current selected pad for instance with: `gROOT->SetSelectedPad(gPad)`.

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

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

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.

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

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

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

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

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

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

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

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

virtual Option_t *	GetOption () const

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

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

Bool_t	HasInconsistentHash () const
	Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.

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

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

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

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

void	InvertBit (UInt_t f)

Bool_t	IsDestructed () const
	IsDestructed.

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

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

R__ALWAYS_INLINE Bool_t	IsOnHeap () const

R__ALWAYS_INLINE Bool_t	IsZombie () const

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).

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

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

void	operator delete (void *ptr)
	Operator delete.

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

void *	operator new (size_t sz)

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

void *	operator new[] (size_t sz)

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

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

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

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

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

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

void	ResetBit (UInt_t f)

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

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

void	SetBit (UInt_t f)

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

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

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

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

R__ALWAYS_INLINE Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

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

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

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

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

Protected Member Functions
void	CopyFrom (TDirectory src, TFile file)

TString	GetMethodOptions (TString methodname, TString methodtitle)
	return the options for the booked method.

ClassificationResult &	GetResults (TString methodname, TString methodtitle)
	Allow to get result for an specific ml method.

TMVA::ROCCurve *	GetROC (TMVA::MethodBase *method, UInt_t iClass=0, TMVA::Types::ETreeType type=TMVA::Types::kTesting)
	Method to get TMVA::ROCCurve Object.

TMVA::ROCCurve *	GetROC (TString methodname, TString methodtitle, UInt_t iClass=0, TMVA::Types::ETreeType type=TMVA::Types::kTesting)
	Method to get TMVA::ROCCurve Object.

Double_t	GetROCIntegral (TString methodname, TString methodtitle, UInt_t iClass=0)
	Method to get ROC-Integral value from mvas.

Bool_t	HasMethodObject (TString methodname, TString methodtitle, Int_t &index)
	Allows to check if the TMVA::MethodBase was created and return the index in the vector.

Bool_t	IsCutsMethod (TMVA::MethodBase *method)
	Allows to check if the ml method is a Cuts method.

void	MergeFiles ()

Protected Member Functions inherited from TMVA::Envelope
	Envelope (const TString &name, DataLoader dataloader=nullptr, TFile file=nullptr, const TString options="")
	timer to measute the time.

DataInputHandler &	GetDataLoaderDataInput ()
	Utility method to get TMVA::DataInputHandler reference from the DataLoader.

DataSetInfo &	GetDataLoaderDataSetInfo ()
	Utility method to get TMVA::DataSetInfo reference from the DataLoader.

DataSetManager *	GetDataLoaderDataSetManager ()
	Utility method to get TMVA::DataSetManager pointer from the DataLoader.

TDirectory *	RootBaseDir ()
	Utility method to get base dir directory from current file.

void	WriteDataInformation (TMVA::DataSetInfo &fDataSetInfo, TMVA::Types::EAnalysisType fAnalysisType)
	method to save Train/Test information into the output file.

Protected Member Functions inherited from TMVA::Configurable
void	EnableLooseOptions (Bool_t b=kTRUE)

const TString &	GetReferenceFile () const

Bool_t	LooseOptionCheckingEnabled () const

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

void	WriteOptionsReferenceToFile ()
	write complete options to output stream

Protected Member Functions inherited from TObject
virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected).

void	MakeZombie ()

Private Attributes
Types::EAnalysisType	fAnalysisType
	vector of objects with booked methods

Bool_t	fCorrelations

std::vector< IMethod * >	fIMethods

std::vector< ClassificationResult >	fResults

Bool_t	fROC

Additional Inherited Members
Public Types inherited from TObject
enum	{ kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff }

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

enum	EDeprecatedStatusBits { kObjInCanvas = BIT(3) }

enum	EStatusBits { kCanDelete = BIT(0) , kMustCleanup = BIT(3) , kIsReferenced = BIT(4) , kHasUUID = BIT(5) , kCannotPick = BIT(6) , kNoContextMenu = BIT(8) , kInvalidObject = BIT(13) }

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

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

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

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

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = BIT(3) }

Protected Attributes inherited from TMVA::Envelope
std::shared_ptr< DataLoader >	fDataLoader
	Booked method information.

std::shared_ptr< TFile >	fFile
	data

UInt_t	fJobs
	procpool object

std::vector< OptionMap >	fMethods

Bool_t	fModelPersistence
	file to save the results

Bool_t	fSilentFile
	List of transformations to test.

TStopwatch	fTimer
	number of jobs to run some high level algorithm in parallel

TString	fTransformations
	flag for extra information

Bool_t	fVerbose
	flag to save the trained model

TProcPool	fWorkers
	if true dont produce file output

Protected Attributes inherited from TMVA::Configurable
MsgLogger *	fLogger

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

#include <TMVA/Classification.h>

Inheritance diagram for TMVA::Experimental::Classification:

[legend]

Constructor & Destructor Documentation

◆ Classification() [1/2]

TMVA::Experimental::Classification::Classification	(	DataLoader *	dataloader,
		TFile *	file,
		TString	options
	)

explicit

Contructor to create a two class classifier.

Parameters

dataloader	TMVA::DataLoader object with the data to train/test.
file	TFile object to save the results
options	string extra options.

Definition at line 181 of file Classification.cxx.

◆ Classification() [2/2]

TMVA::Experimental::Classification::Classification	(	DataLoader *	dataloader,
		TString	options
	)

explicit

Contructor to create a two class classifier without output file.

Parameters

dataloader	TMVA::DataLoader object with the data to train/test.
options	string extra options.

Definition at line 200 of file Classification.cxx.

◆ ~Classification()

TMVA::Experimental::Classification::~Classification ( )

Definition at line 219 of file Classification.cxx.

Member Function Documentation

◆ CopyFrom()

void TMVA::Experimental::Classification::CopyFrom	(	TDirectory *	src,
		TFile *	file
	)

protected

Definition at line 1092 of file Classification.cxx.

◆ Evaluate()

void TMVA::Experimental::Classification::Evaluate ( )

virtual

Method to perform Train/Test over all ml method booked.

If the option Jobs > 1 can do it in parallel with MultiProc.

Implements TMVA::Envelope.

Definition at line 248 of file Classification.cxx.

◆ GetMethod()

TMVA::MethodBase * TMVA::Experimental::Classification::GetMethod	(	TString	methodname,
		TString	methodtitle
	)

Return a TMVA::MethodBase object.

if method is not booked then return a null pointer.

Parameters

methodname	name of the method.
methodtitle	method title.

Returns: TMVA::MethodBase object

Definition at line 385 of file Classification.cxx.

◆ GetMethodOptions()

TString TMVA::Experimental::Classification::GetMethodOptions	(	TString	methodname,
		TString	methodtitle
	)

protected

return the options for the booked method.

Parameters

methodname	name of the method.
methodtitle	method title.

Returns: string the with options for the ml method.

Definition at line 234 of file Classification.cxx.

◆ GetResults() [1/2]

std::vector< TMVA::Experimental::ClassificationResult > & TMVA::Experimental::Classification::GetResults ( )

return the the vector of TMVA::Experimental::ClassificationResult objects.

Returns: vector of results.

Definition at line 944 of file Classification.cxx.

◆ GetResults() [2/2]

TMVA::Experimental::ClassificationResult & TMVA::Experimental::Classification::GetResults	(	TString	methodname,
		TString	methodtitle
	)

protected

Allow to get result for an specific ml method.

Parameters

methodname	name of the method.
methodtitle	method title.

Returns: TMVA::Experimental::ClassificationResult object for the method.

Definition at line 969 of file Classification.cxx.

◆ GetROC() [1/2]

TMVA::ROCCurve * TMVA::Experimental::Classification::GetROC	(	TMVA::MethodBase *	method,
		UInt_t	iClass = `0`,
		TMVA::Types::ETreeType	type = `TMVA::Types::kTesting`
	)

protected

Method to get TMVA::ROCCurve Object.

Parameters

method	TMVA::MethodBase object
iClass	category, default 0 then signal
type	train/test tree, default test.

Returns: TMVA::ROCCurve object.

Definition at line 992 of file Classification.cxx.

◆ GetROC() [2/2]

TMVA::ROCCurve * TMVA::Experimental::Classification::GetROC	(	TString	methodname,
		TString	methodtitle,
		UInt_t	iClass = `0`,
		TMVA::Types::ETreeType	type = `TMVA::Types::kTesting`
	)

protected

Method to get TMVA::ROCCurve Object.

Parameters

methodname	ml method name.
methodtitle	ml method title.
iClass	category, default 0 then signal
type	train/test tree, default test.

Returns: TMVA::ROCCurve object.

Definition at line 1059 of file Classification.cxx.

◆ GetROCIntegral()

Double_t TMVA::Experimental::Classification::GetROCIntegral	(	TString	methodname,
		TString	methodtitle,
		UInt_t	iClass = `0`
	)

protected

Method to get ROC-Integral value from mvas.

Parameters

methodname	ml method name.
methodtitle	ml method title.
iClass	category, default 0 then signal

Returns: Double_t with the ROC-Integral value.

Definition at line 1073 of file Classification.cxx.

◆ HasMethodObject()

Bool_t TMVA::Experimental::Classification::HasMethodObject	(	TString	methodname,
		TString	methodtitle,
		Int_t &	index
	)

protected

Allows to check if the TMVA::MethodBase was created and return the index in the vector.

Parameters

methodname	name of the method.
methodtitle	method title.
index	refrence to Int_t with the position of the method into the vector fIMethods

Returns: boolean true if the method was found.

Definition at line 493 of file Classification.cxx.

◆ IsCutsMethod()

Bool_t TMVA::Experimental::Classification::IsCutsMethod ( TMVA::MethodBase * method )

protected

Allows to check if the ml method is a Cuts method.

Returns: boolen true if the method is a Cuts method.

Definition at line 956 of file Classification.cxx.

◆ MergeFiles()

void TMVA::Experimental::Classification::MergeFiles ( )

protected

Definition at line 1129 of file Classification.cxx.

◆ Test()

void TMVA::Experimental::Classification::Test ( )

virtual

Perform test evaluation in all booked methods.

Definition at line 512 of file Classification.cxx.

◆ TestMethod() [1/2]

void TMVA::Experimental::Classification::TestMethod	(	TString	methodname,
		TString	methodtitle
	)

virtual

Lets perform test an specific ml method.

Parameters

methodname	name of the method.
methodtitle	method title.

Definition at line 525 of file Classification.cxx.

◆ TestMethod() [2/2]

void TMVA::Experimental::Classification::TestMethod	(	Types::EMVA	method,
		TString	methodtitle
	)

virtual

Lets perform test an specific ml method given the method type in enum TMVA::Types::EMVA.

Parameters

method	TMVA::Types::EMVA type.
methodtitle	method title.

Definition at line 934 of file Classification.cxx.

◆ Train()

void TMVA::Experimental::Classification::Train ( )

virtual

Method to train all booked ml methods.

Definition at line 323 of file Classification.cxx.

◆ TrainMethod() [1/2]

void TMVA::Experimental::Classification::TrainMethod	(	TString	methodname,
		TString	methodtitle
	)

virtual

Lets train an specific ml method.

Parameters

methodname	name of the method.
methodtitle	method title.

Definition at line 336 of file Classification.cxx.

◆ TrainMethod() [2/2]

void TMVA::Experimental::Classification::TrainMethod	(	Types::EMVA	method,
		TString	methodtitle
	)

virtual

Lets train an specific ml method given the method type in enum TMVA::Types::EMVA.

Parameters

method	TMVA::Types::EMVA type.
methodtitle	method title.

Definition at line 372 of file Classification.cxx.

Member Data Documentation

◆ fAnalysisType

Types::EAnalysisType TMVA::Experimental::Classification::fAnalysisType

private

vector of objects with booked methods

Definition at line 166 of file Classification.h.

◆ fCorrelations

Bool_t TMVA::Experimental::Classification::fCorrelations

private

Definition at line 167 of file Classification.h.

◆ fIMethods

std::vector<IMethod *> TMVA::Experimental::Classification::fIMethods

private

Definition at line 165 of file Classification.h.

◆ fResults

std::vector<ClassificationResult> TMVA::Experimental::Classification::fResults

private

Definition at line 164 of file Classification.h.

◆ fROC

Bool_t TMVA::Experimental::Classification::fROC

private

Definition at line 168 of file Classification.h.

Libraries for TMVA::Experimental::Classification:

[legend]

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

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

Public Member Functions

Protected Member Functions

Private Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ Classification() [1/2]

◆ Classification() [2/2]

◆ ~Classification()

Member Function Documentation

◆ CopyFrom()

◆ Evaluate()

◆ GetMethod()

◆ GetMethodOptions()

◆ GetResults() [1/2]

◆ GetResults() [2/2]

◆ GetROC() [1/2]

◆ GetROC() [2/2]

◆ GetROCIntegral()

◆ HasMethodObject()

◆ IsCutsMethod()

◆ MergeFiles()

◆ Test()

◆ TestMethod() [1/2]

◆ TestMethod() [2/2]

◆ Train()

◆ TrainMethod() [1/2]

◆ TrainMethod() [2/2]

Member Data Documentation

◆ fAnalysisType

◆ fCorrelations

◆ fIMethods

◆ fResults

◆ fROC