TMVA::DataSet Class Reference

Definition at line 80 of file DataSet.h.

Public Member Functions
	DataSet (const DataSetInfo &)
	constructor More...
virtual	~DataSet ()
	destructor More...
void	AddEvent (Event *, Types::ETreeType)
	add event to event list after which the event is owned by the dataset More...
Long64_t	GetNEvents (Types::ETreeType type=Types::kMaxTreeType) const
Long64_t	GetNTrainingEvents () const
Long64_t	GetNTestEvents () const
const Event *	GetEvent () const
const Event *	GetEvent (Long64_t ievt) const
const Event *	GetTrainingEvent (Long64_t ievt) const
const Event *	GetTestEvent (Long64_t ievt) const
const Event *	GetEvent (Long64_t ievt, Types::ETreeType type) const
UInt_t	GetNVariables () const
	access the number of variables through the datasetinfo More...
UInt_t	GetNTargets () const
	access the number of targets through the datasetinfo More...
UInt_t	GetNSpectators () const
	access the number of targets through the datasetinfo More...
void	SetCurrentEvent (Long64_t ievt) const
void	SetCurrentType (Types::ETreeType type) const
Types::ETreeType	GetCurrentType () const
void	SetEventCollection (std::vector< Event *> *, Types::ETreeType)
	Sets the event collection (by DataSetFactory) More...
const std::vector< Event * > &	GetEventCollection (Types::ETreeType type=Types::kMaxTreeType) const
const TTree *	GetEventCollectionAsTree ()
Long64_t	GetNEvtSigTest ()
	return number of signal test events in dataset More...
Long64_t	GetNEvtBkgdTest ()
	return number of background test events in dataset More...
Long64_t	GetNEvtSigTrain ()
	return number of signal training events in dataset More...
Long64_t	GetNEvtBkgdTrain ()
	return number of background training events in dataset More...
Bool_t	HasNegativeEventWeights () const
Results *	GetResults (const TString &, Types::ETreeType type, Types::EAnalysisType analysistype)
	TString info(resultsName+"/"); switch(type) { case Types::kTraining: info += "kTraining/"; break; case Types::kTesting: info += "kTesting/"; break; default: break; } switch(analysistype) { case Types::kClassification: info += "kClassification"; break; case Types::kRegression: info += "kRegression"; break; case Types::kNoAnalysisType: info += "kNoAnalysisType"; break; case Types::kMaxAnalysisType:info += "kMaxAnalysisType"; break; }. More...
void	DeleteResults (const TString &, Types::ETreeType type, Types::EAnalysisType analysistype)
	delete the results stored for this particulary Method instance (here appareantly called resultsName instead of MethodTitle Tree type (Training, testing etc..) Analysis Type (Classification, Multiclass, Regression etc..) More...
void	SetVerbose (Bool_t)
void	DivideTrainingSet (UInt_t blockNum)
	divide training set More...
void	MoveTrainingBlock (Int_t blockInd, Types::ETreeType dest, Bool_t applyChanges=kTRUE)
	move training block More...
void	IncrementNClassEvents (Int_t type, UInt_t classNumber)
Long64_t	GetNClassEvents (Int_t type, UInt_t classNumber)
void	ClearNClassEvents (Int_t type)
TTree *	GetTree (Types::ETreeType type)
	create the test/trainings tree with all the variables, the weights, the classes, the targets, the spectators, the MVA outputs More...
void	InitSampling (Float_t fraction, Float_t weight, UInt_t seed=0)
	initialize random or importance sampling More...
void	EventResult (Bool_t successful, Long64_t evtNumber=-1)
	increase the importance sampling weight of the event when not successful and decrease it when successful More...
void	CreateSampling () const
	create an event sampling (random or importance sampling) More...
UInt_t	TreeIndex (Types::ETreeType type) const

Private Member Functions
	DataSet ()
void	DestroyCollection (Types::ETreeType type, Bool_t deleteEvents)
	destroys the event collection (events + vector) More...
MsgLogger &	Log () const
void	ApplyTrainingBlockDivision ()
void	ApplyTrainingSetDivision ()
	apply division of data set More...

Private Attributes
const DataSetInfo &	fdsi
std::vector< Event * >::iterator	fEvtCollIt
	datasetinfo that created this dataset More...
std::vector< std::vector< Event * > *>	fEventCollection
std::vector< std::map< TString, Results *> >	fResults
	list of events for training/testing/... More...
UInt_t	fCurrentTreeIdx
	[train/test/...][method-identifier] More...
Long64_t	fCurrentEventIdx
std::vector< Char_t >	fSampling
std::vector< Int_t >	fSamplingNEvents
std::vector< Float_t >	fSamplingWeight
std::vector< std::vector< std::pair< Float_t, Long64_t > *> >	fSamplingEventList
std::vector< std::vector< std::pair< Float_t, Long64_t > *> >	fSamplingSelected
TRandom3 *	fSamplingRandom
std::vector< std::vector< Long64_t > >	fClassEvents
Bool_t	fHasNegativeEventWeights
	number of events of class 0,1,2,... in training[0] More...
MsgLogger *	fLogger
std::vector< Char_t >	fBlockBelongToTraining
Long64_t	fTrainingBlockSize

#include <TMVA/DataSet.h>

Collaboration diagram for TMVA::DataSet:

Constructor & Destructor Documentation

DataSet() [1/2]

TMVA::DataSet::DataSet

(

const DataSetInfo &

dsi

)

constructor

Definition at line 61 of file DataSet.cxx.

~DataSet()

TMVA::DataSet::~DataSet ( )

virtual

destructor

Definition at line 94 of file DataSet.cxx.

DataSet() [2/2]

TMVA::DataSet::DataSet ( )

private

Referenced by SetVerbose().

Member Function Documentation

AddEvent()

void TMVA::DataSet::AddEvent	(	Event *	ev,
		Types::ETreeType	type
	)

add event to event list after which the event is owned by the dataset

Definition at line 219 of file DataSet.cxx.

ApplyTrainingBlockDivision()

void TMVA::DataSet::ApplyTrainingBlockDivision ( )

private

ApplyTrainingSetDivision()

void TMVA::DataSet::ApplyTrainingSetDivision ( )

private

apply division of data set

Definition at line 358 of file DataSet.cxx.

Referenced by DivideTrainingSet(), and MoveTrainingBlock().

ClearNClassEvents()

void TMVA::DataSet::ClearNClassEvents

(

Int_t

type

)

Definition at line 138 of file DataSet.cxx.

Referenced by SetEventCollection(), and SetVerbose().

CreateSampling()

void TMVA::DataSet::CreateSampling

(

)

const

create an event sampling (random or importance sampling)

Definition at line 472 of file DataSet.cxx.

Referenced by TMVA::MethodMLP::BackPropagationMinimize(), TMVA::MethodMLP::BFGSMinimize(), and SetVerbose().

DeleteResults()

void TMVA::DataSet::DeleteResults	(	const TString &	resultsName,
		Types::ETreeType	type,
		Types::EAnalysisType	analysistype
	)

delete the results stored for this particulary Method instance (here appareantly called resultsName instead of MethodTitle Tree type (Training, testing etc..) Analysis Type (Classification, Multiclass, Regression etc..)

Definition at line 308 of file DataSet.cxx.

Referenced by HasNegativeEventWeights(), and TMVA::MethodBDT::Reset().

DestroyCollection()

void TMVA::DataSet::DestroyCollection ( Types::ETreeType  type, Bool_t  deleteEvents  )

private

destroys the event collection (events + vector)

Definition at line 167 of file DataSet.cxx.

Referenced by SetEventCollection(), SetVerbose(), and ~DataSet().

DivideTrainingSet()

void TMVA::DataSet::DivideTrainingSet

(

UInt_t

blockNum

)

divide training set

Definition at line 334 of file DataSet.cxx.

Referenced by SetVerbose().

EventResult()

void TMVA::DataSet::EventResult	(	Bool_t	successful,
		Long64_t	evtNumber = -1
	)

increase the importance sampling weight of the event when not successful and decrease it when successful

Definition at line 536 of file DataSet.cxx.

Referenced by TMVA::MethodMLP::BackPropagationMinimize(), TMVA::MethodMLP::BFGSMinimize(), and SetVerbose().

GetCurrentType()

TMVA::Types::ETreeType TMVA::DataSet::GetCurrentType ( ) const

inline

Definition at line 213 of file DataSet.h.

Referenced by TMVA::MethodMLP::CalculateEstimator(), TMVA::MethodMLP::ComputeDEDw(), CreateSampling(), TMVA::MethodMLP::GetError(), GetTree(), InitSampling(), SetCurrentType(), TMVA::MethodBase::Statistics(), TMVA::MethodBase::TestRegression(), and TMVA::MethodMLP::TrainOneEpoch().

GetEvent() [1/3]

const TMVA::Event * TMVA::DataSet::GetEvent

(

)

const

Definition at line 180 of file DataSet.cxx.

Referenced by TMVA::MethodBoost::AdaBoost(), TMVA::MethodBoost::Bagging(), TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::MethodHMatrix::ComputeCovariance(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::MethodBase::CreateMVAPdfs(), TMVA::MethodLikelihood::CreateRanking(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), TMVA::MethodHMatrix::GetChi2(), GetEvent(), TMVA::MethodPyAdaBoost::GetMvaValue(), TMVA::MethodPyGTB::GetMvaValue(), TMVA::MethodPyRandomForest::GetMvaValue(), GetNTestEvents(), GetTestEvent(), GetTrainingEvent(), GetTree(), TMVA::RMethodBase::LoadData(), TMVA::ResultsRegression::QuadraticDeviation(), TMVA::MethodBoost::ResetBoostWeights(), TMVA::MethodBase::TestRegression(), TMVA::MethodDT::TestTreeQuality(), TMVA::CCTreeWrapper::TestTreeQuality(), and TMVA::MethodLikelihood::Train().

GetEvent() [2/3]

const Event* TMVA::DataSet::GetEvent ( Long64_t  ievt ) const

inline

Definition at line 95 of file DataSet.h.

Referenced by GetEvent().

GetEvent() [3/3]

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

inline

Definition at line 98 of file DataSet.h.

GetEventCollection()

const std::vector< TMVA::Event * > & TMVA::DataSet::GetEventCollection ( Types::ETreeType  type = Types::kMaxTreeType ) const

inline

Definition at line 235 of file DataSet.h.

Referenced by TMVA::MethodBase::GetEventCollection(), TMVA::OptimizeConfigParameters::GetMVADists(), GetNEvents(), SetCurrentType(), and TMVA::Factory::WriteDataInformation().

GetEventCollectionAsTree()

const TTree* TMVA::DataSet::GetEventCollectionAsTree

(

)

Referenced by SetCurrentType().

GetNClassEvents()

Long64_t TMVA::DataSet::GetNClassEvents	(	Int_t	type,
		UInt_t	classNumber
	)

Definition at line 146 of file DataSet.cxx.

Referenced by TMVA::DataSetFactory::BuildInitialDataSet(), GetNEvtBkgdTest(), GetNEvtBkgdTrain(), GetNEvtSigTest(), GetNEvtSigTrain(), and SetVerbose().

GetNEvents()

Long64_t TMVA::DataSet::GetNEvents ( Types::ETreeType  type = Types::kMaxTreeType ) const

inline

Definition at line 225 of file DataSet.h.

Referenced by TMVA::MethodBase::AddClassifierOutput(), TMVA::MethodBase::AddClassifierOutputProb(), TMVA::MethodBase::AddMulticlassOutput(), TMVA::MethodBase::AddRegressionOutput(), TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::DataSetFactory::CreateDataSet(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::MethodCuts::CreateVariablePDFs(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), TMVA::MethodBoost::FindMVACut(), TMVA::MethodFisher::GetCov_WithinClass(), TMVA::MethodBase::GetEfficiency(), TMVA::MethodFisher::GetMean(), TMVA::MethodBase::GetNEvents(), GetNTestEvents(), GetNTrainingEvents(), TMVA::MethodLD::GetSum(), TMVA::MethodLD::GetSumVal(), TMVA::MethodBase::GetTrainingEfficiency(), GetTree(), TMVA::MethodRuleFit::InitEventSample(), InitSampling(), TMVA::MethodMLP::ProcessOptions(), TMVA::ResultsRegression::QuadraticDeviation(), TMVA::MethodBase::Statistics(), TMVA::MethodDT::TestTreeQuality(), TMVA::CCTreeWrapper::TestTreeQuality(), TMVA::MethodTMlpANN::Train(), TMVA::MethodSVM::Train(), TMVA::MethodLikelihood::Train(), TMVA::MethodCuts::Train(), TMVA::MethodBase::TrainMethod(), TMVA::MethodMLP::TrainOneEpoch(), and TMVA::RuleFitAPI::WriteTest().

GetNEvtBkgdTest()

Long64_t TMVA::DataSet::GetNEvtBkgdTest

(

)

return number of background test events in dataset

Definition at line 398 of file DataSet.cxx.

Referenced by TMVA::Factory::EvaluateAllMethods(), and SetCurrentType().

GetNEvtBkgdTrain()

Long64_t TMVA::DataSet::GetNEvtBkgdTrain

(

)

return number of background training events in dataset

Definition at line 414 of file DataSet.cxx.

Referenced by SetCurrentType(), TMVA::MethodRSVM::Train(), TMVA::MethodTMlpANN::Train(), and TMVA::MethodPDEFoam::Train().

GetNEvtSigTest()

Long64_t TMVA::DataSet::GetNEvtSigTest

(

)

return number of signal test events in dataset

Definition at line 390 of file DataSet.cxx.

Referenced by TMVA::Factory::EvaluateAllMethods(), TMVA::MethodCuts::GetEfficiency(), and SetCurrentType().

GetNEvtSigTrain()

Long64_t TMVA::DataSet::GetNEvtSigTrain

(

)

return number of signal training events in dataset

Definition at line 406 of file DataSet.cxx.

Referenced by SetCurrentType(), TMVA::MethodRSVM::Train(), TMVA::MethodTMlpANN::Train(), and TMVA::MethodPDEFoam::Train().

GetNSpectators()

UInt_t TMVA::DataSet::GetNSpectators

(

)

const

access the number of targets through the datasetinfo

Definition at line 210 of file DataSet.cxx.

Referenced by TMVA::DataSetFactory::CalcMinMax(), and GetEvent().

GetNTargets()

UInt_t TMVA::DataSet::GetNTargets

(

)

const

access the number of targets through the datasetinfo

Definition at line 202 of file DataSet.cxx.

Referenced by TMVA::DataSetFactory::CalcMinMax(), TMVA::MethodPDEFoam::CalcXminXmax(), GetEvent(), TMVA::MethodPDEFoam::GetRegressionValues(), TMVA::MethodPDEFoam::InitFoam(), TMVA::MethodPDEFoam::ReadWeightsFromStream(), TMVA::MethodPDEFoam::ReadWeightsFromXML(), TMVA::MethodPDEFoam::SetXminXmax(), TMVA::MethodPDEFoam::TrainMonoTargetRegression(), and TMVA::MethodPDEFoam::TrainMultiTargetRegression().

GetNTestEvents()

Long64_t TMVA::DataSet::GetNTestEvents ( ) const

inline

Definition at line 91 of file DataSet.h.

Referenced by TMVA::MethodBDT::BoostMonitor(), TMVA::RMethodBase::LoadData(), TMVA::DataSetFactory::MixEvents(), TMVA::RuleFitAPI::ReadYhat(), and TMVA::RuleFitAPI::SetTestParms().

GetNTrainingEvents()

Long64_t TMVA::DataSet::GetNTrainingEvents ( ) const

inline

Definition at line 90 of file DataSet.h.

Referenced by TMVA::MethodPDEFoam::CalcXminXmax(), TMVA::MethodLikelihood::CreateRanking(), TMVA::MethodPDERS::GetSample(), TMVA::MethodBase::HasTrainingTree(), TMVA::MethodPyGTB::Init(), TMVA::MethodPyRandomForest::Init(), TMVA::MethodPyAdaBoost::Init(), TMVA::MethodBDT::InitEventSample(), TMVA::RuleFit::Initialize(), TMVA::RMethodBase::LoadData(), TMVA::DataSetFactory::MixEvents(), TMVA::Factory::OptimizeAllMethods(), TMVA::MethodDT::ProcessOptions(), TMVA::MethodBDT::ProcessOptions(), TMVA::MethodCFMlpANN::ProcessOptions(), TMVA::MethodRuleFit::ProcessOptions(), TMVA::RuleFitAPI::SetTrainParms(), TMVA::MethodDT::Train(), TMVA::MethodCategory::Train(), TMVA::Factory::TrainAllMethods(), TMVA::MethodRuleFit::TrainJFRuleFit(), TMVA::MethodBase::WriteStateToStream(), and TMVA::RuleFitAPI::WriteTrain().

GetNVariables()

UInt_t TMVA::DataSet::GetNVariables

(

)

const

access the number of variables through the datasetinfo

Definition at line 194 of file DataSet.cxx.

Referenced by TMVA::DataSetFactory::CalcCorrelationMatrix(), TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::MethodPDEFoam::CalcXminXmax(), GetEvent(), TMVA::MethodTMlpANN::GetMvaValue(), TMVA::MethodPyGTB::Init(), TMVA::MethodPyAdaBoost::Init(), TMVA::MethodPyRandomForest::Init(), TMVA::MethodPDEFoam::InitFoam(), TMVA::MethodTMlpANN::ReadWeightsFromStream(), TMVA::MethodCuts::ReadWeightsFromStream(), TMVA::MethodTMlpANN::ReadWeightsFromXML(), TMVA::MethodCuts::Train(), and TMVA::MethodPDEFoam::TrainMultiTargetRegression().

GetResults()

TMVA::Results * TMVA::DataSet::GetResults	(	const TString &	resultsName,
		Types::ETreeType	type,
		Types::EAnalysisType	analysistype
	)

TString info(resultsName+"/"); switch(type) { case Types::kTraining: info += "kTraining/"; break; case Types::kTesting: info += "kTesting/"; break; default: break; } switch(analysistype) { case Types::kClassification: info += "kClassification"; break; case Types::kRegression: info += "kRegression"; break; case Types::kNoAnalysisType: info += "kNoAnalysisType"; break; case Types::kMaxAnalysisType:info += "kMaxAnalysisType"; break; }.

Definition at line 257 of file DataSet.cxx.

Referenced by TMVA::MethodBoost::AdaBoost(), TMVA::MethodBDT::AdaBoost(), TMVA::MethodBDT::AdaBoostR2(), TMVA::MethodBDT::AdaCost(), TMVA::MethodBase::AddClassifierOutput(), TMVA::MethodBase::AddClassifierOutputProb(), TMVA::MethodBase::AddMulticlassOutput(), TMVA::MethodBase::AddRegressionOutput(), TMVA::MethodBDT::BoostMonitor(), TMVA::MethodBase::CreateMVAPdfs(), TMVA::Factory::EvaluateAllMethods(), TMVA::MethodBoost::FindMVACut(), TMVA::MethodCuts::GetEfficiency(), TMVA::MethodBase::GetEfficiency(), TMVA::MethodBase::GetKSTrainingVsTest(), TMVA::MethodBase::GetMaximumSignificance(), TMVA::MethodBase::GetMulticlassEfficiency(), TMVA::MethodBase::GetMulticlassTrainingEfficiency(), TMVA::MethodBase::GetRegressionDeviation(), TMVA::MethodCuts::GetTrainingEfficiency(), TMVA::MethodBase::GetTrainingEfficiency(), HasNegativeEventWeights(), TMVA::MethodBoost::InitHistos(), TMVA::MethodBoost::MonitorBoost(), TMVA::MethodBase::TestClassification(), TMVA::MethodBase::TestMulticlass(), TMVA::MethodBoost::Train(), TMVA::MethodBDT::Train(), and TMVA::MethodBase::WriteEvaluationHistosToFile().

GetTestEvent()

const Event* TMVA::DataSet::GetTestEvent ( Long64_t  ievt ) const

inline

Definition at line 97 of file DataSet.h.

GetTrainingEvent()

const Event* TMVA::DataSet::GetTrainingEvent ( Long64_t  ievt ) const

inline

Definition at line 96 of file DataSet.h.

Referenced by TMVA::MethodPyAdaBoost::Init(), TMVA::MethodPyRandomForest::Init(), and TMVA::MethodPyGTB::Init().

GetTree()

TTree * TMVA::DataSet::GetTree

(

Types::ETreeType

type

)

create the test/trainings tree with all the variables, the weights, the classes, the targets, the spectators, the MVA outputs

Definition at line 573 of file DataSet.cxx.

Referenced by TMVA::Factory::EvaluateAllMethods(), and SetVerbose().

HasNegativeEventWeights()

Bool_t TMVA::DataSet::HasNegativeEventWeights ( ) const

inline

Definition at line 123 of file DataSet.h.

IncrementNClassEvents()

void TMVA::DataSet::IncrementNClassEvents	(	Int_t	type,
		UInt_t	classNumber
	)

Definition at line 129 of file DataSet.cxx.

Referenced by SetEventCollection(), and SetVerbose().

InitSampling()

void TMVA::DataSet::InitSampling	(	Float_t	fraction,
		Float_t	weight,
		UInt_t	seed = 0
	)

initialize random or importance sampling

Definition at line 422 of file DataSet.cxx.

Referenced by TMVA::MethodMLP::BackPropagationMinimize(), TMVA::MethodMLP::BFGSMinimize(), and SetVerbose().

Log()

MsgLogger& TMVA::DataSet::Log ( ) const

inlineprivate

Definition at line 186 of file DataSet.h.

Referenced by CreateSampling(), DeleteResults(), EventResult(), GetNClassEvents(), and GetTree().

MoveTrainingBlock()

void TMVA::DataSet::MoveTrainingBlock	(	Int_t	blockInd,
		Types::ETreeType	dest,
		Bool_t	applyChanges = kTRUE
	)

move training block

Definition at line 378 of file DataSet.cxx.

Referenced by SetVerbose().

SetCurrentEvent()

void TMVA::DataSet::SetCurrentEvent ( Long64_t  ievt ) const

inline

Definition at line 110 of file DataSet.h.

Referenced by TMVA::MethodBase::AddClassifierOutput(), TMVA::MethodBase::AddClassifierOutputProb(), TMVA::MethodBase::AddMulticlassOutput(), TMVA::MethodBase::AddRegressionOutput(), TMVA::DataSetFactory::BuildDynamicDataSet(), and TMVA::MethodBase::GetTrainingEfficiency().

SetCurrentType()

void TMVA::DataSet::SetCurrentType ( Types::ETreeType  type ) const

inline

Definition at line 111 of file DataSet.h.

Referenced by TMVA::MethodBase::AddClassifierOutput(), TMVA::MethodBase::AddClassifierOutputProb(), TMVA::MethodBase::AddMulticlassOutput(), TMVA::MethodBase::AddRegressionOutput(), TMVA::MethodMLP::BackPropagationMinimize(), TMVA::MethodMLP::BFGSMinimize(), TMVA::DataSetFactory::BuildDynamicDataSet(), TMVA::MethodBoost::CalcMVAValues(), TMVA::MethodMLP::CalculateEstimator(), TMVA::MethodHMatrix::ComputeCovariance(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::MethodBase::CreateMVAPdfs(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), TMVA::MethodBoost::GetBoostROCIntegral(), TMVA::MethodCuts::GetEfficiency(), TMVA::MethodBase::GetEfficiency(), TMVA::MethodBase::GetMulticlassEfficiency(), TMVA::MethodBase::GetMulticlassTrainingEfficiency(), TMVA::MethodBase::GetTrainingEfficiency(), GetTree(), TMVA::MethodBDT::InitEventSample(), TMVA::RuleFit::Initialize(), TMVA::MethodBoost::MonitorBoost(), TMVA::MethodMLP::ProcessOptions(), TMVA::ResultsRegression::QuadraticDeviation(), TMVA::MethodBoost::SingleTrain(), TMVA::MethodBase::Statistics(), TMVA::MethodBoost::TestClassification(), TMVA::MethodBase::TestClassification(), TMVA::MethodBase::TestRegression(), TMVA::MethodDT::TestTreeQuality(), TMVA::CCTreeWrapper::TestTreeQuality(), TMVA::MethodDT::Train(), TMVA::MethodSVM::Train(), TMVA::MethodBoost::Train(), TMVA::MethodRuleFit::TrainJFRuleFit(), TMVA::MethodBase::TrainMethod(), and TMVA::RuleFitAPI::WriteTest().

SetEventCollection()

void TMVA::DataSet::SetEventCollection	(	std::vector< Event *> *	events,
		Types::ETreeType	type
	)

Sets the event collection (by DataSetFactory)

Definition at line 229 of file DataSet.cxx.

Referenced by TMVA::DataSetFactory::BuildDynamicDataSet(), TMVA::DataSetFactory::MixEvents(), and SetCurrentType().

SetVerbose()

void TMVA::DataSet::SetVerbose ( Bool_t  )

inline

Definition at line 132 of file DataSet.h.

TreeIndex()

UInt_t TMVA::DataSet::TreeIndex ( Types::ETreeType  type ) const

inline

Definition at line 200 of file DataSet.h.

Referenced by ApplyTrainingSetDivision(), CreateSampling(), DestroyCollection(), DivideTrainingSet(), GetEvent(), GetEventCollection(), TMVA::MethodBase::GetEventCollection(), GetNEvents(), GetResults(), GetTree(), InitSampling(), SetCurrentType(), SetEventCollection(), and SetVerbose().

Member Data Documentation

fBlockBelongToTraining

std::vector<Char_t> TMVA::DataSet::fBlockBelongToTraining

private

Definition at line 187 of file DataSet.h.

Referenced by ApplyTrainingSetDivision(), DataSet(), DivideTrainingSet(), MoveTrainingBlock(), and ~DataSet().

fClassEvents

std::vector< std::vector<Long64_t> > TMVA::DataSet::fClassEvents

private

Definition at line 180 of file DataSet.h.

Referenced by ClearNClassEvents(), DataSet(), DivideTrainingSet(), GetNClassEvents(), and IncrementNClassEvents().

fCurrentEventIdx

Long64_t TMVA::DataSet::fCurrentEventIdx

mutableprivate

Definition at line 168 of file DataSet.h.

Referenced by GetEvent(), and SetCurrentEvent().

fCurrentTreeIdx

UInt_t TMVA::DataSet::fCurrentTreeIdx

mutableprivate

[train/test/...][method-identifier]

Definition at line 167 of file DataSet.h.

Referenced by AddEvent(), EventResult(), GetCurrentType(), GetEvent(), SetCurrentType(), SetEventCollection(), and TreeIndex().

fdsi

const DataSetInfo& TMVA::DataSet::fdsi

private

Definition at line 160 of file DataSet.h.

Referenced by GetNClassEvents(), GetNEvtBkgdTest(), GetNEvtBkgdTrain(), GetNEvtSigTest(), GetNEvtSigTrain(), GetNSpectators(), GetNTargets(), GetNVariables(), GetResults(), and GetTree().

fEventCollection

std::vector< std::vector<Event*>* > TMVA::DataSet::fEventCollection

private

Definition at line 163 of file DataSet.h.

Referenced by AddEvent(), ApplyTrainingSetDivision(), DestroyCollection(), DivideTrainingSet(), GetEvent(), GetEventCollection(), and SetEventCollection().

fEvtCollIt

std::vector<Event*>::iterator TMVA::DataSet::fEvtCollIt

private

datasetinfo that created this dataset

Definition at line 162 of file DataSet.h.

Referenced by AddEvent(), and SetEventCollection().

fHasNegativeEventWeights

Bool_t TMVA::DataSet::fHasNegativeEventWeights

private

number of events of class 0,1,2,... in training[0]

Definition at line 183 of file DataSet.h.

Referenced by AddEvent(), and HasNegativeEventWeights().

fLogger

MsgLogger* TMVA::DataSet::fLogger

mutableprivate

Definition at line 185 of file DataSet.h.

Referenced by Log(), and ~DataSet().

fResults

std::vector< std::map< TString, Results* > > TMVA::DataSet::fResults

private

list of events for training/testing/...

Definition at line 165 of file DataSet.h.

Referenced by DeleteResults(), GetResults(), GetTree(), and ~DataSet().

fSampling

std::vector<Char_t> TMVA::DataSet::fSampling

private

Definition at line 171 of file DataSet.h.

Referenced by CreateSampling(), DataSet(), EventResult(), GetEvent(), GetNEvents(), and InitSampling().

fSamplingEventList

std::vector< std::vector< std::pair< Float_t, Long64_t >* > > TMVA::DataSet::fSamplingEventList

mutableprivate

Definition at line 174 of file DataSet.h.

Referenced by CreateSampling(), EventResult(), InitSampling(), and ~DataSet().

fSamplingNEvents

std::vector<Int_t> TMVA::DataSet::fSamplingNEvents

private

Definition at line 172 of file DataSet.h.

Referenced by CreateSampling(), DataSet(), and InitSampling().

fSamplingRandom

TRandom3* TMVA::DataSet::fSamplingRandom

private

Definition at line 176 of file DataSet.h.

Referenced by CreateSampling(), DataSet(), InitSampling(), and ~DataSet().

fSamplingSelected

std::vector< std::vector< std::pair< Float_t, Long64_t >* > > TMVA::DataSet::fSamplingSelected

mutableprivate

Definition at line 175 of file DataSet.h.

Referenced by CreateSampling(), GetEvent(), GetNEvents(), and InitSampling().

fSamplingWeight

std::vector<Float_t> TMVA::DataSet::fSamplingWeight

private

Definition at line 173 of file DataSet.h.

Referenced by DataSet(), EventResult(), and InitSampling().

fTrainingBlockSize

Long64_t TMVA::DataSet::fTrainingBlockSize

private

Definition at line 191 of file DataSet.h.

---

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

• tmva/tmva/inc/TMVA/DataSet.h
• tmva/tmva/src/DataSet.cxx