Class for boosting a TMVA method.

This class is meant to boost a single classifier. Boosting means training the classifier a few times. Every time the weights of the events are modified according to how well the classifier performed on the test sample.

Definition at line 58 of file MethodBoost.h.

Public Member Functions
	MethodBoost (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")

	MethodBoost (DataSetInfo &dsi, const TString &theWeightFile)

virtual	~MethodBoost (void)
	destructor

Bool_t	BookMethod (Types::EMVA theMethod, TString methodTitle, TString theOption)
	just registering the string from which the boosted classifier will be created

void	CleanBoostOptions ()

const Ranking *	CreateRanking ()

Int_t	GetBoostNum ()

Double_t	GetMvaValue (Double_t err=nullptr, Double_t errUpper=nullptr)
	return boosted MVA response

virtual Bool_t	HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
	Boost can handle classification with 2 classes and regression with one regression-target.

virtual TClass *	IsA () const

void	SetBoostedMethodName (TString methodName)

virtual void	Streamer (TBuffer &)

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

void	Train (void)

Public Member Functions inherited from TMVA::MethodCompositeBase
	MethodCompositeBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")

	MethodCompositeBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)

virtual	~MethodCompositeBase (void)
	delete methods

void	AddWeightsXMLTo (void *parent) const

Double_t	GetMvaValue (const TMVA::Event const ev, Double_t err=nullptr, Double_t *errUpper=nullptr)

Double_t	GetMvaValue (Double_t err=nullptr, Double_t errUpper=nullptr)
	return composite MVA response

virtual Double_t	GetMvaValue (Double_t errLower=nullptr, Double_t errUpper=nullptr)=0

virtual void	ReadWeightsFromStream (std::istream &)=0

void	ReadWeightsFromStream (std::istream &istr)
	text streamer

virtual void	ReadWeightsFromStream (TFile &)

void	ReadWeightsFromXML (void *wghtnode)
	XML streamer.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Public Member Functions inherited from TMVA::MethodBase
	MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="")
	standard constructor

	MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)
	constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles

virtual	~MethodBase ()
	destructor

void	AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)

TDirectory *	BaseDir () const
	returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored

DataSet *	Data () const

DataSetInfo &	DataInfo () const

void	DisableWriting (Bool_t setter)

Bool_t	DoMulticlass () const

Bool_t	DoRegression () const

void	ExitFromTraining ()

Types::EAnalysisType	GetAnalysisType () const

UInt_t	GetCurrentIter ()

virtual Double_t	GetEfficiency (const TString &, Types::ETreeType, Double_t &err)
	fill background efficiency (resp.

const Event *	GetEvent () const

const Event *	GetEvent (const TMVA::Event *ev) const

const Event *	GetEvent (Long64_t ievt) const

const Event *	GetEvent (Long64_t ievt, Types::ETreeType type) const

const std::vector< TMVA::Event * > &	GetEventCollection (Types::ETreeType type)
	returns the event collection (i.e.

TFile *	GetFile () const

const TString &	GetInputLabel (Int_t i) const

const char *	GetInputTitle (Int_t i) const

const TString &	GetInputVar (Int_t i) const

TMultiGraph *	GetInteractiveTrainingError ()

const TString &	GetJobName () const

virtual Double_t	GetKSTrainingVsTest (Char_t SorB, TString opt="X")

virtual Double_t	GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
	plot significance, \( \frac{S}{\sqrt{S^2 + B^2}} \), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance

UInt_t	GetMaxIter ()

Double_t	GetMean (Int_t ivar) const

const TString &	GetMethodName () const

Types::EMVA	GetMethodType () const

TString	GetMethodTypeName () const

virtual TMatrixD	GetMulticlassConfusionMatrix (Double_t effB, Types::ETreeType type)
	Construct a confusion matrix for a multiclass classifier.

virtual std::vector< Float_t >	GetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)

virtual std::vector< Float_t >	GetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)

virtual const std::vector< Float_t > &	GetMulticlassValues ()

Double_t	GetMvaValue (const TMVA::Event const ev, Double_t err=nullptr, Double_t *errUpper=nullptr)

const char *	GetName () const

UInt_t	GetNEvents () const

UInt_t	GetNTargets () const

UInt_t	GetNvar () const

UInt_t	GetNVariables () const

virtual Double_t	GetProba (const Event *ev)

virtual Double_t	GetProba (Double_t mvaVal, Double_t ap_sig)
	compute likelihood ratio

const TString	GetProbaName () const

virtual Double_t	GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
	compute rarity:

virtual void	GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const

virtual const std::vector< Float_t > &	GetRegressionValues ()

const std::vector< Float_t > &	GetRegressionValues (const TMVA::Event *const ev)

Double_t	GetRMS (Int_t ivar) const

virtual Double_t	GetROCIntegral (PDF pdfS=nullptr, PDF pdfB=nullptr) const
	calculate the area (integral) under the ROC curve as a overall quality measure of the classification

virtual Double_t	GetROCIntegral (TH1D histS, TH1D histB) const
	calculate the area (integral) under the ROC curve as a overall quality measure of the classification

virtual Double_t	GetSeparation (PDF pdfS=nullptr, PDF pdfB=nullptr) const
	compute "separation" defined as

virtual Double_t	GetSeparation (TH1 , TH1 ) const
	compute "separation" defined as

Double_t	GetSignalReferenceCut () const

Double_t	GetSignalReferenceCutOrientation () const

virtual Double_t	GetSignificance () const
	compute significance of mean difference

const Event *	GetTestingEvent (Long64_t ievt) const

Double_t	GetTestTime () const

const TString &	GetTestvarName () const

virtual Double_t	GetTrainingEfficiency (const TString &)

const Event *	GetTrainingEvent (Long64_t ievt) const

virtual const std::vector< Float_t > &	GetTrainingHistory (const char *)

UInt_t	GetTrainingROOTVersionCode () const

TString	GetTrainingROOTVersionString () const
	calculates the ROOT version string from the training version code on the fly

UInt_t	GetTrainingTMVAVersionCode () const

TString	GetTrainingTMVAVersionString () const
	calculates the TMVA version string from the training version code on the fly

Double_t	GetTrainTime () const

TransformationHandler &	GetTransformationHandler (Bool_t takeReroutedIfAvailable=true)

const TransformationHandler &	GetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const

TString	GetWeightFileName () const
	retrieve weight file name

Double_t	GetXmax (Int_t ivar) const

Double_t	GetXmin (Int_t ivar) const

Bool_t	HasMVAPdfs () const

void	InitIPythonInteractive ()

Bool_t	IsModelPersistence () const

virtual Bool_t	IsSignalLike ()
	uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background

virtual Bool_t	IsSignalLike (Double_t mvaVal)
	uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would be selected as signal or background

Bool_t	IsSilentFile () const

virtual void	MakeClass (const TString &classFileName=TString("")) const
	create reader class for method (classification only at present)

TDirectory *	MethodBaseDir () const
	returns the ROOT directory where all instances of the corresponding MVA method are stored

virtual std::map< TString, Double_t >	OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
	call the Optimizer with the set of parameters and ranges that are meant to be tuned.

void	PrintHelpMessage () const
	prints out method-specific help method

void	ProcessSetup ()
	process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

void	ReadStateFromFile ()
	Function to write options and weights to file.

void	ReadStateFromStream (std::istream &tf)
	read the header from the weight files of the different MVA methods

void	ReadStateFromStream (TFile &rf)
	write reference MVA distributions (and other information) to a ROOT type weight file

void	ReadStateFromXMLString (const char *xmlstr)
	for reading from memory

void	RerouteTransformationHandler (TransformationHandler *fTargetTransformation)

virtual void	Reset ()

virtual void	SetAnalysisType (Types::EAnalysisType type)

void	SetBaseDir (TDirectory *methodDir)

void	SetFile (TFile *file)

void	SetMethodBaseDir (TDirectory *methodDir)

void	SetMethodDir (TDirectory *methodDir)

void	SetModelPersistence (Bool_t status)

void	SetSignalReferenceCut (Double_t cut)

void	SetSignalReferenceCutOrientation (Double_t cutOrientation)

void	SetSilentFile (Bool_t status)

void	SetTestTime (Double_t testTime)

void	SetTestvarName (const TString &v="")

void	SetTrainTime (Double_t trainTime)

virtual void	SetTuneParameters (std::map< TString, Double_t > tuneParameters)
	set the tuning parameters according to the argument This is just a dummy .

void	SetupMethod ()
	setup of methods

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

virtual void	TestMulticlass ()
	test multiclass classification

virtual void	TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
	calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample

bool	TrainingEnded ()

void	TrainMethod ()

void	WriteStateToFile () const
	write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created

Public Member Functions inherited from TMVA::IMethod
	IMethod ()

virtual	~IMethod ()

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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

virtual void	ParseOptions ()
	options parser

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	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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.

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

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

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

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

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

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

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

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

TClass *	IsA () const override

Bool_t	IsSortable () const override

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

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

void	Print (Option_t *option="") const override
	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.

void	Streamer (TBuffer &) override
	Stream an object of class TObject.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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 with: `gROOT->SetSelectedPad(c1)`.

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=nullptr)
	Execute method on this object with the given parameter string, e.g.

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=nullptr)
	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 (the base implementation is no-op).

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, void vp)
	Only called by placement new when throwing an exception.

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

void	operator delete[] (void ptr, void vp)
	Only called by placement new[] when throwing an exception.

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.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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=nullptr, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory.

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

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TMVA::MethodCompositeBase
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TMVA::MethodBase
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TMVA::IMethod
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TMVA::Configurable
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TNamed
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TObject
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

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 Member Functions
void	GetHelpMessage () const
	Get help message text.

Protected Member Functions inherited from TMVA::MethodCompositeBase
MethodBase *	GetCurrentMethod ()

MethodBase *	GetCurrentMethod (UInt_t idx)

UInt_t	GetCurrentMethodIndex ()

IMethod *	GetLastMethod ()

IMethod *	GetMethod (const Int_t index) const
	accessor by index in vector

IMethod *	GetMethod (const TString &title) const
	accessor by name

IMethod *	GetPreviousMethod ()

Protected Member Functions inherited from TMVA::MethodBase
virtual std::vector< Double_t >	GetDataMvaValues (DataSet *data=nullptr, Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
	get all the MVA values for the events of the given Data type

const TString &	GetInternalVarName (Int_t ivar) const

virtual std::vector< Double_t >	GetMvaValues (Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
	get all the MVA values for the events of the current Data type

const TString &	GetOriginalVarName (Int_t ivar) const

const TString &	GetWeightFileDir () const

Bool_t	HasTrainingTree () const

Bool_t	Help () const

Bool_t	IgnoreEventsWithNegWeightsInTraining () const

Bool_t	IsConstructedFromWeightFile () const

Bool_t	IsNormalised () const

virtual void	MakeClassSpecific (std::ostream &, const TString &="") const

virtual void	MakeClassSpecificHeader (std::ostream &, const TString &="") const

void	NoErrorCalc (Double_t const err, Double_t const errUpper)

void	SetNormalised (Bool_t norm)

void	SetWeightFileDir (TString fileDir)
	set directory of weight file

void	SetWeightFileName (TString)
	set the weight file name (depreciated)

void	Statistics (Types::ETreeType treeType, const TString &theVarName, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &)
	calculates rms,mean, xmin, xmax of the event variable this can be either done for the variables as they are or for normalised variables (in the range of 0-1) if "norm" is set to kTRUE

Bool_t	TxtWeightsOnly () const

Bool_t	Verbose () const

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 Member Functions
Double_t	AdaBoost (MethodBase *method, Bool_t useYesNoLeaf)
	the standard (discrete or real) AdaBoost algorithm

Double_t	Bagging ()
	Bagging or Bootstrap boosting, gives new random poisson weight for every event.

Double_t	CalcMethodWeight ()

void	CalcMVAValues ()

void	CheckSetup ()
	check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

void	ClearAll ()

void	CreateMVAHistorgrams ()

MethodBase *	CurrentMethod ()

UInt_t	CurrentMethodIdx ()

void	DeclareCompatibilityOptions ()
	options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weight file at hand

void	DeclareOptions ()

void	FindMVACut (MethodBase *method)
	find the CUT on the individual MVA that defines an event as correct or misclassified (to be used in the boosting process)

Double_t	GetBoostROCIntegral (Bool_t, Types::ETreeType, Bool_t CalcOverlapIntergral=kFALSE)
	Calculate the ROC integral of a single classifier or even the whole boosted classifier.

void	Init ()

void	InitHistos ()
	initialisation routine

void	MonitorBoost (Types::EBoostStage stage, UInt_t methodIdx=0)
	fill various monitoring histograms from information of the individual classifiers that have been boosted.

void	PrintResults (const TString &, std::vector< Double_t > &, const Double_t) const

void	ProcessOptions ()
	process user options

void	ResetBoostWeights ()
	resetting back the boosted weights of the events to 1

Double_t	SingleBoost (MethodBase *method)

void	SingleTrain ()
	initialization

virtual void	TestClassification ()
	initialization

virtual void	WriteEvaluationHistosToFile (Types::ETreeType treetype)
	writes all MVA evaluation histograms to file

void	WriteMonitoringHistosToFile (void) const
	write special monitoring histograms to file dummy implementation here --------------—

Private Attributes
Double_t	fAdaBoostBeta
	ADA boost parameter, default is 1.

Double_t	fBaggedSampleFraction
	rel.Size of bagged sample

TString	fBoostedMethodName
	details of the boosted classifier

TString	fBoostedMethodOptions
	options

TString	fBoostedMethodTitle
	title

UInt_t	fBoostNum
	Number of times the classifier is boosted.

TString	fBoostType
	string specifying the boost type

Double_t	fBoostWeight
	the weight used to boost the next classifier

std::vector< TH1 * >	fBTrainBgdMVAHist

std::vector< TH1 * >	fBTrainSigMVAHist

DataSetManager *	fDataSetManager
	DSMTEST.

Bool_t	fDetailedMonitoring
	produce detailed monitoring histograms (boost-wise)

Bool_t	fHistoricBoolOption
	historic variable, only needed for "CompatibilityOptions"

TString	fHistoricOption
	historic variable, only needed for "CompatibilityOptions"

Double_t	fMethodError
	estimation of the level error of the classifier

Bool_t	fMonitorBoostedMethod
	monitor the MVA response of every classifier

TTree *	fMonitorTree
	tree to monitor values during the boosting

std::vector< Float_t > *	fMVAvalues
	mva values for the last trained method

Double_t	fOverlap_integral

UInt_t	fRandomSeed
	seed for random number generator used for bagging

Double_t	fROC_training
	roc integral of last trained method (on training sample)

std::vector< TH1 * >	fTestBgdMVAHist

std::vector< TH1 * >	fTestSigMVAHist

std::vector< TH1 * >	fTrainBgdMVAHist

std::vector< TH1 * >	fTrainSigMVAHist

TString	fTransformString
	min and max values for the classifier response

Friends
class	Experimental::Classification

class	Factory

class	Reader

Additional Inherited Members
Public Types inherited from TMVA::MethodBase
enum	EWeightFileType { kROOT =0 , kTEXT }

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

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

enum	EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }

enum	EStatusBits { kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) , kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 )) }

Public Attributes inherited from TMVA::MethodBase
Bool_t	fSetupCompleted

TrainingHistory	fTrainHistory

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = (1ULL << ( 3 )) }

Protected Attributes inherited from TMVA::MethodCompositeBase
MethodBase *	fCurrentMethod

UInt_t	fCurrentMethodIdx

std::vector< IMethod * >	fMethods
	vector of all classifiers

std::vector< Double_t >	fMethodWeight

Protected Attributes inherited from TMVA::MethodBase
Types::EAnalysisType	fAnalysisType

UInt_t	fBackgroundClass

bool	fExitFromTraining = false

std::vector< TString > *	fInputVars

IPythonInteractive *	fInteractive = nullptr
	temporary dataset used when evaluating on a different data (used by MethodCategory::GetMvaValues)

UInt_t	fIPyCurrentIter = 0

UInt_t	fIPyMaxIter = 0

std::vector< Float_t > *	fMulticlassReturnVal

Int_t	fNbins

Int_t	fNbinsH

Int_t	fNbinsMVAoutput

Ranking *	fRanking

std::vector< Float_t > *	fRegressionReturnVal

Results *	fResults

UInt_t	fSignalClass

DataSet *	fTmpData = nullptr
	temporary event when testing on a different DataSet than the own one

const Event *	fTmpEvent

Protected Attributes inherited from TMVA::Configurable
MsgLogger *	fLogger
	! message logger

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

#include <TMVA/MethodBoost.h>

Inheritance diagram for TMVA::MethodBoost:

[legend]

Constructor & Destructor Documentation

◆ MethodBoost() [1/2]

TMVA::MethodBoost::MethodBoost	(	const TString &	jobName,
		const TString &	methodTitle,
		DataSetInfo &	theData,
		const TString &	theOption = "" )

Definition at line 90 of file MethodBoost.cxx.

◆ MethodBoost() [2/2]

TMVA::MethodBoost::MethodBoost	(	DataSetInfo &	dsi,
		const TString &	theWeightFile )

Definition at line 117 of file MethodBoost.cxx.

◆ ~MethodBoost()

TMVA::MethodBoost::~MethodBoost ( void )

virtual

destructor

Definition at line 143 of file MethodBoost.cxx.

Member Function Documentation

◆ AdaBoost()

Double_t TMVA::MethodBoost::AdaBoost	(	MethodBase *	method,
		Bool_t	useYesNoLeaf )

private

the standard (discrete or real) AdaBoost algorithm

Definition at line 867 of file MethodBoost.cxx.

◆ Bagging()

Double_t TMVA::MethodBoost::Bagging ( )

private

Bagging or Bootstrap boosting, gives new random poisson weight for every event.

Definition at line 1031 of file MethodBoost.cxx.

◆ BookMethod()

Bool_t TMVA::MethodBoost::BookMethod	(	Types::EMVA	theMethod,
		TString	methodTitle,
		TString	theOption )

just registering the string from which the boosted classifier will be created

Definition at line 250 of file MethodBoost.cxx.

◆ CalcMethodWeight()

Double_t TMVA::MethodBoost::CalcMethodWeight ( )

private

◆ CalcMVAValues()

void TMVA::MethodBoost::CalcMVAValues ( )

private

Definition at line 1277 of file MethodBoost.cxx.

◆ CheckSetup()

void TMVA::MethodBoost::CheckSetup ( )

privatevirtual

check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

Reimplemented from TMVA::MethodBase.

Definition at line 328 of file MethodBoost.cxx.

◆ Class()

static TClass * TMVA::MethodBoost::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * TMVA::MethodBoost::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t TMVA::MethodBoost::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 202 of file MethodBoost.h.

◆ CleanBoostOptions()

void TMVA::MethodBoost::CleanBoostOptions ( )

Definition at line 531 of file MethodBoost.cxx.

◆ ClearAll()

void TMVA::MethodBoost::ClearAll ( )

private

◆ CreateMVAHistorgrams()

void TMVA::MethodBoost::CreateMVAHistorgrams ( )

private

Definition at line 538 of file MethodBoost.cxx.

◆ CreateRanking()

const TMVA::Ranking * TMVA::MethodBoost::CreateRanking ( )

virtual

Implements TMVA::MethodCompositeBase.

Definition at line 1087 of file MethodBoost.cxx.

◆ CurrentMethod()

MethodBase * TMVA::MethodBoost::CurrentMethod ( )

inlineprivate

Definition at line 114 of file MethodBoost.h.

◆ CurrentMethodIdx()

UInt_t TMVA::MethodBoost::CurrentMethodIdx ( )

inlineprivate

Definition at line 115 of file MethodBoost.h.

◆ DeclareCompatibilityOptions()

void TMVA::MethodBoost::DeclareCompatibilityOptions ( )

privatevirtual

options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weight file at hand

Reimplemented from TMVA::MethodBase.

Definition at line 215 of file MethodBoost.cxx.

◆ DeclareOptions()

void TMVA::MethodBoost::DeclareOptions ( )

privatevirtual

Implements TMVA::MethodCompositeBase.

Definition at line 176 of file MethodBoost.cxx.

◆ DeclFileName()

static const char * TMVA::MethodBoost::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 202 of file MethodBoost.h.

◆ FindMVACut()

void TMVA::MethodBoost::FindMVACut ( MethodBase * method )

private

find the CUT on the individual MVA that defines an event as correct or misclassified (to be used in the boosting process)

Definition at line 690 of file MethodBoost.cxx.

◆ GetBoostNum()

Int_t TMVA::MethodBoost::GetBoostNum ( )

inline

Definition at line 88 of file MethodBoost.h.

◆ GetBoostROCIntegral()

Double_t TMVA::MethodBoost::GetBoostROCIntegral	(	Bool_t	singleMethod,
		Types::ETreeType	eTT,
		Bool_t	CalcOverlapIntergral = kFALSE )

private

Calculate the ROC integral of a single classifier or even the whole boosted classifier.

The tree type (training or testing sample) is specified by 'eTT'.

If tree type kTraining is set, the original training sample is used to compute the ROC integral (original weights).

singleMethod - if kTRUE, return ROC integral of single (last trained) classifier; if kFALSE, return ROC integral of full classifier
eTT - tree type (Types::kTraining / Types::kTesting)
CalcOverlapIntergral - if kTRUE, the overlap integral of the signal/background MVA distributions is calculated and stored in 'fOverlap_integral'

Definition at line 1156 of file MethodBoost.cxx.

◆ GetHelpMessage()

void TMVA::MethodBoost::GetHelpMessage ( ) const

protectedvirtual

Get help message text.

typical length of text line: "|--------------------------------------------------------------|"

Implements TMVA::IMethod.

Definition at line 1049 of file MethodBoost.cxx.

◆ GetMvaValue()

Double_t TMVA::MethodBoost::GetMvaValue	(	Double_t *	err = nullptr,
		Double_t *	errUpper = nullptr )

virtual

return boosted MVA response

Implements TMVA::MethodBase.

Definition at line 1095 of file MethodBoost.cxx.

◆ HasAnalysisType()

Bool_t TMVA::MethodBoost::HasAnalysisType	(	Types::EAnalysisType	type,
		UInt_t	numberClasses,
		UInt_t	)

virtual

Boost can handle classification with 2 classes and regression with one regression-target.

Implements TMVA::IMethod.

Definition at line 166 of file MethodBoost.cxx.

◆ Init()

void TMVA::MethodBoost::Init ( void )

privatevirtual

Implements TMVA::MethodBase.

Definition at line 264 of file MethodBoost.cxx.

◆ InitHistos()

void TMVA::MethodBoost::InitHistos ( )

private

initialisation routine

Definition at line 271 of file MethodBoost.cxx.

◆ IsA()

virtual TClass * TMVA::MethodBoost::IsA ( ) const

inlinevirtual

Returns: TClass describing current object

Reimplemented from TMVA::MethodCompositeBase.

Definition at line 202 of file MethodBoost.h.

◆ MonitorBoost()

void TMVA::MethodBoost::MonitorBoost	(	Types::EBoostStage	stage,
		UInt_t	methodIndex = 0 )

private

fill various monitoring histograms from information of the individual classifiers that have been boosted.

of course.... this depends very much on the individual classifiers, and so far, only for Decision Trees, this monitoring is actually implemented

Definition at line 1305 of file MethodBoost.cxx.

◆ PrintResults()

void TMVA::MethodBoost::PrintResults	(	const TString &	,
		std::vector< Double_t > &	,
		const Double_t	) const

private

◆ ProcessOptions()

void TMVA::MethodBoost::ProcessOptions ( )

privatevirtual

process user options

Implements TMVA::MethodCompositeBase.

Definition at line 663 of file MethodBoost.cxx.

◆ ResetBoostWeights()

void TMVA::MethodBoost::ResetBoostWeights ( )

private

resetting back the boosted weights of the events to 1

Definition at line 569 of file MethodBoost.cxx.

◆ SetBoostedMethodName()

void TMVA::MethodBoost::SetBoostedMethodName ( TString methodName )

inline

Definition at line 86 of file MethodBoost.h.

◆ SingleBoost()

Double_t TMVA::MethodBoost::SingleBoost ( MethodBase * method )

private

Definition at line 850 of file MethodBoost.cxx.

◆ SingleTrain()

void TMVA::MethodBoost::SingleTrain ( )

private

initialization

Definition at line 670 of file MethodBoost.cxx.

◆ Streamer()

virtual void TMVA::MethodBoost::Streamer ( TBuffer & )

virtual

Reimplemented from TMVA::MethodCompositeBase.

◆ StreamerNVirtual()

void TMVA::MethodBoost::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 202 of file MethodBoost.h.

◆ TestClassification()

void TMVA::MethodBoost::TestClassification ( )

privatevirtual

initialization

Reimplemented from TMVA::MethodBase.

Definition at line 609 of file MethodBoost.cxx.

◆ Train()

void TMVA::MethodBoost::Train ( void )

virtual

Implements TMVA::MethodCompositeBase.

Definition at line 351 of file MethodBoost.cxx.

◆ WriteEvaluationHistosToFile()

void TMVA::MethodBoost::WriteEvaluationHistosToFile ( Types::ETreeType treetype )

privatevirtual

writes all MVA evaluation histograms to file

Reimplemented from TMVA::MethodBase.

Definition at line 637 of file MethodBoost.cxx.

◆ WriteMonitoringHistosToFile()

void TMVA::MethodBoost::WriteMonitoringHistosToFile ( void ) const

privatevirtual

write special monitoring histograms to file dummy implementation here --------------—

Reimplemented from TMVA::MethodBase.

Definition at line 579 of file MethodBoost.cxx.

Friends And Related Symbol Documentation

◆ Experimental::Classification

friend class Experimental::Classification

friend

Definition at line 61 of file MethodBoost.h.

◆ Factory

friend class Factory

friend

Definition at line 59 of file MethodBoost.h.

◆ Reader

friend class Reader

friend

Definition at line 60 of file MethodBoost.h.

Member Data Documentation

◆ fAdaBoostBeta

Double_t TMVA::MethodBoost::fAdaBoostBeta

private

ADA boost parameter, default is 1.

Definition at line 159 of file MethodBoost.h.

◆ fBaggedSampleFraction

Double_t TMVA::MethodBoost::fBaggedSampleFraction

private

rel.Size of bagged sample

Definition at line 161 of file MethodBoost.h.

◆ fBoostedMethodName

TString TMVA::MethodBoost::fBoostedMethodName

private

details of the boosted classifier

Definition at line 163 of file MethodBoost.h.

◆ fBoostedMethodOptions

TString TMVA::MethodBoost::fBoostedMethodOptions

private

options

Definition at line 165 of file MethodBoost.h.

◆ fBoostedMethodTitle

TString TMVA::MethodBoost::fBoostedMethodTitle

private

title

Definition at line 164 of file MethodBoost.h.

◆ fBoostNum

UInt_t TMVA::MethodBoost::fBoostNum

private

Number of times the classifier is boosted.

Definition at line 153 of file MethodBoost.h.

◆ fBoostType

TString TMVA::MethodBoost::fBoostType

private

string specifying the boost type

Definition at line 154 of file MethodBoost.h.

◆ fBoostWeight

Double_t TMVA::MethodBoost::fBoostWeight

private

the weight used to boost the next classifier

Definition at line 182 of file MethodBoost.h.

◆ fBTrainBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fBTrainBgdMVAHist

private

Definition at line 174 of file MethodBoost.h.

◆ fBTrainSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fBTrainSigMVAHist

private

Definition at line 173 of file MethodBoost.h.

◆ fDataSetManager

DataSetManager* TMVA::MethodBoost::fDataSetManager

private

DSMTEST.

Definition at line 193 of file MethodBoost.h.

◆ fDetailedMonitoring

Bool_t TMVA::MethodBoost::fDetailedMonitoring

private

produce detailed monitoring histograms (boost-wise)

Definition at line 157 of file MethodBoost.h.

◆ fHistoricBoolOption

Bool_t TMVA::MethodBoost::fHistoricBoolOption

private

historic variable, only needed for "CompatibilityOptions"

Definition at line 195 of file MethodBoost.h.

◆ fHistoricOption

TString TMVA::MethodBoost::fHistoricOption

private

historic variable, only needed for "CompatibilityOptions"

Definition at line 194 of file MethodBoost.h.

◆ fMethodError

Double_t TMVA::MethodBoost::fMethodError

private

estimation of the level error of the classifier

Definition at line 183 of file MethodBoost.h.

◆ fMonitorBoostedMethod

Bool_t TMVA::MethodBoost::fMonitorBoostedMethod

private

monitor the MVA response of every classifier

Definition at line 167 of file MethodBoost.h.

◆ fMonitorTree

TTree* TMVA::MethodBoost::fMonitorTree

private

tree to monitor values during the boosting

Definition at line 181 of file MethodBoost.h.

◆ fMVAvalues

std::vector<Float_t>* TMVA::MethodBoost::fMVAvalues

private

mva values for the last trained method

Definition at line 191 of file MethodBoost.h.

◆ fOverlap_integral

Double_t TMVA::MethodBoost::fOverlap_integral

private

Definition at line 189 of file MethodBoost.h.

◆ fRandomSeed

UInt_t TMVA::MethodBoost::fRandomSeed

private

seed for random number generator used for bagging

Definition at line 160 of file MethodBoost.h.

◆ fROC_training

Double_t TMVA::MethodBoost::fROC_training

private

roc integral of last trained method (on training sample)

Definition at line 185 of file MethodBoost.h.

◆ fTestBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTestBgdMVAHist

private

Definition at line 178 of file MethodBoost.h.

◆ fTestSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTestSigMVAHist

private

Definition at line 176 of file MethodBoost.h.

◆ fTrainBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTrainBgdMVAHist

private

Definition at line 171 of file MethodBoost.h.

◆ fTrainSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTrainSigMVAHist

private

Definition at line 170 of file MethodBoost.h.

◆ fTransformString

TString TMVA::MethodBoost::fTransformString

private

min and max values for the classifier response

Definition at line 156 of file MethodBoost.h.

Libraries for TMVA::MethodBoost:

[legend]

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

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

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Constructor & Destructor Documentation

◆ MethodBoost() [1/2]

◆ MethodBoost() [2/2]

◆ ~MethodBoost()

Member Function Documentation

◆ AdaBoost()

◆ Bagging()

◆ BookMethod()

◆ CalcMethodWeight()

◆ CalcMVAValues()

◆ CheckSetup()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ CleanBoostOptions()

◆ ClearAll()

◆ CreateMVAHistorgrams()

◆ CreateRanking()

◆ CurrentMethod()

◆ CurrentMethodIdx()

◆ DeclareCompatibilityOptions()

◆ DeclareOptions()

◆ DeclFileName()

◆ FindMVACut()

◆ GetBoostNum()

◆ GetBoostROCIntegral()

◆ GetHelpMessage()

◆ GetMvaValue()

◆ HasAnalysisType()

◆ Init()

◆ InitHistos()

◆ IsA()

◆ MonitorBoost()

◆ PrintResults()

◆ ProcessOptions()

◆ ResetBoostWeights()

◆ SetBoostedMethodName()

◆ SingleBoost()

◆ SingleTrain()

◆ Streamer()

◆ StreamerNVirtual()

◆ TestClassification()

◆ Train()

◆ WriteEvaluationHistosToFile()

◆ WriteMonitoringHistosToFile()

Friends And Related Symbol Documentation

◆ Experimental::Classification

◆ Factory

◆ Reader

Member Data Documentation

◆ fAdaBoostBeta

◆ fBaggedSampleFraction

◆ fBoostedMethodName

◆ fBoostedMethodOptions

◆ fBoostedMethodTitle

◆ fBoostNum

◆ fBoostType

◆ fBoostWeight

◆ fBTrainBgdMVAHist

◆ fBTrainSigMVAHist

◆ fDataSetManager

◆ fDetailedMonitoring

◆ fHistoricBoolOption

◆ fHistoricOption

◆ fMethodError

◆ fMonitorBoostedMethod

◆ fMonitorTree

◆ fMVAvalues

◆ fOverlap_integral

◆ fRandomSeed

◆ fROC_training

◆ fTestBgdMVAHist

◆ fTestSigMVAHist