TMVA::MethodBDT

TMVA::MethodBDT Class Reference

#include <MethodBDT.h>

Inheritance diagram for TMVA::MethodBDT:

TMVA::MethodBase TMVA::MethodBase TMVA::Configurable TMVA::IMethod TMVA::Configurable TMVA::IMethod TMVA::Configurable TMVA::IMethod TMVA::Configurable TMVA::IMethod List of all members.

Public Member Functions

 MethodBDT (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="", TDirectory *theTargetDir=0)
 MethodBDT (DataSetInfo &theData, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
virtual ~MethodBDT (void)
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
void InitEventSample ()
virtual std::map< TString,
Double_t > 		OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
void Train (void)
void Reset (void)
void AddWeightsXMLTo (void *parent) const
void ReadWeightsFromStream (istream &istr)
void ReadWeightsFromXML (void *parent)
void WriteMonitoringHistosToFile (void) const
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
const std::vector< Float_t > & GetMulticlassValues ()
const std::vector< Float_t > & GetRegressionValues ()
Double_t Boost (std::vector< TMVA::Event * >, DecisionTree *dt, Int_t iTree, UInt_t cls=0)
const Ranking * CreateRanking ()
void DeclareOptions ()
void ProcessOptions ()
void SetMaxDepth (Int_t d)
void SetNodeMinEvents (Int_t d)
void SetNTrees (Int_t d)
void SetAdaBoostBeta (Double_t b)
void SetNodePurityLimit (Double_t l)
const std::vector< TMVA::DecisionTree * > & GetForest () const
const std::vector< TMVA::Event * > & GetTrainingEvents () const
const std::vector< double > & GetBoostWeights () const
std::vector< Double_t > GetVariableImportance ()
Double_t GetVariableImportance (UInt_t ivar)
Double_t TestTreeQuality (DecisionTree *dt)
void MakeClassSpecific (std::ostream &, const TString &) const
void MakeClassSpecificHeader (std::ostream &, const TString &) const
void MakeClassInstantiateNode (DecisionTreeNode *n, std::ostream &fout, const TString &className) const
void GetHelpMessage () const
virtual Bool_t IsSignalLike ()
 MethodBDT (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="", TDirectory *theTargetDir=0)
 MethodBDT (DataSetInfo &theData, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
virtual ~MethodBDT (void)
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
void InitEventSample ()
virtual std::map< TString,
Double_t > 		OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
void Train (void)
void Reset (void)
void AddWeightsXMLTo (void *parent) const
void ReadWeightsFromStream (istream &istr)
void ReadWeightsFromXML (void *parent)
void WriteMonitoringHistosToFile (void) const
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
const std::vector< Float_t > & GetMulticlassValues ()
const std::vector< Float_t > & GetRegressionValues ()
Double_t Boost (std::vector< TMVA::Event * >, DecisionTree *dt, Int_t iTree, UInt_t cls=0)
const Ranking * CreateRanking ()
void DeclareOptions ()
void ProcessOptions ()
void SetMaxDepth (Int_t d)
void SetNodeMinEvents (Int_t d)
void SetNTrees (Int_t d)
void SetAdaBoostBeta (Double_t b)
void SetNodePurityLimit (Double_t l)
const std::vector< TMVA::DecisionTree * > & GetForest () const
const std::vector< TMVA::Event * > & GetTrainingEvents () const
const std::vector< double > & GetBoostWeights () const
std::vector< Double_t > GetVariableImportance ()
Double_t GetVariableImportance (UInt_t ivar)
Double_t TestTreeQuality (DecisionTree *dt)
void MakeClassSpecific (std::ostream &, const TString &) const
void MakeClassSpecificHeader (std::ostream &, const TString &) const
void MakeClassInstantiateNode (DecisionTreeNode *n, std::ostream &fout, const TString &className) const
void GetHelpMessage () const
virtual Bool_t IsSignalLike ()

Protected Member Functions

void DeclareCompatibilityOptions ()
void DeclareCompatibilityOptions ()

Private Member Functions

Double_t GetMvaValue (Double_t *err, Double_t *errUpper, UInt_t useNTrees)
void Init (void)
Double_t AdaBoost (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t Bagging (std::vector< TMVA::Event * >, Int_t iTree)
Double_t RegBoost (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t AdaBoostR2 (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t GradBoost (std::vector< TMVA::Event * >, DecisionTree *dt, UInt_t cls=0)
Double_t GradBoostRegression (std::vector< TMVA::Event * >, DecisionTree *dt)
void InitGradBoost (std::vector< TMVA::Event * >)
void UpdateTargets (std::vector< TMVA::Event * >, UInt_t cls=0)
void UpdateTargetsRegression (std::vector< TMVA::Event * >, Bool_t first=kFALSE)
Double_t GetGradBoostMVA (TMVA::Event &e, UInt_t nTrees)
void GetRandomSubSample ()
Double_t GetWeightedQuantile (std::vector< std::pair< Double_t, Double_t > > vec, const Double_t quantile, const Double_t SumOfWeights=0.0)
Double_t GetMvaValue (Double_t *err, Double_t *errUpper, UInt_t useNTrees)
void Init (void)
Double_t AdaBoost (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t Bagging (std::vector< TMVA::Event * >, Int_t iTree)
Double_t RegBoost (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t AdaBoostR2 (std::vector< TMVA::Event * >, DecisionTree *dt)
Double_t GradBoost (std::vector< TMVA::Event * >, DecisionTree *dt, UInt_t cls=0)
Double_t GradBoostRegression (std::vector< TMVA::Event * >, DecisionTree *dt)
void InitGradBoost (std::vector< TMVA::Event * >)
void UpdateTargets (std::vector< TMVA::Event * >, UInt_t cls=0)
void UpdateTargetsRegression (std::vector< TMVA::Event * >, Bool_t first=kFALSE)
Double_t GetGradBoostMVA (TMVA::Event &e, UInt_t nTrees)
void GetRandomSubSample ()
Double_t GetWeightedQuantile (std::vector< std::pair< Double_t, Double_t > > vec, const Double_t quantile, const Double_t SumOfWeights=0.0)

Private Attributes

std::vector< TMVA::Event * > fEventSample
std::vector< TMVA::Event * > fValidationSample
std::vector< TMVA::Event * > fSubSample
Int_t fNTrees
std::vector< DecisionTree * > fForest
std::vector< double > fBoostWeights
Bool_t fRenormByClass
TString fBoostType
Double_t fAdaBoostBeta
TString fAdaBoostR2Loss
Double_t fTransitionPoint
Double_t fShrinkage
Bool_t fBaggedGradBoost
Double_t fSampleFraction
Double_t fSumOfWeights
std::map< TMVA::Event *, std::pair<
Double_t, Double_t > > 		fWeightedResiduals
std::map< TMVA::Event *, std::vector<
double > > 		fResiduals
SeparationBase * fSepType
TString fSepTypeS
Int_t fNodeMinEvents
Int_t fNCuts
Bool_t fUseFisherCuts
Double_t fMinLinCorrForFisher
Bool_t fUseExclusiveVars
Bool_t fUseYesNoLeaf
Double_t fNodePurityLimit
Bool_t fUseWeightedTrees
UInt_t fNNodesMax
UInt_t fMaxDepth
DecisionTree::EPruneMethod fPruneMethod
TString fPruneMethodS
Double_t fPruneStrength
Bool_t fPruneBeforeBoost
Double_t fFValidationEvents
Bool_t fAutomatic
Bool_t fRandomisedTrees
UInt_t fUseNvars
Bool_t fUsePoissonNvars
UInt_t fUseNTrainEvents
Double_t fSampleSizeFraction
Bool_t fNoNegWeightsInTraining
TTree * fMonitorNtuple
Int_t fITree
Double_t fBoostWeight
Double_t fErrorFraction
std::vector< Double_t > fVariableImportance
std::vector< TMVA::Event * > fEventSample
std::vector< TMVA::Event * > fValidationSample
std::vector< TMVA::Event * > fSubSample
std::vector< DecisionTree * > fForest
std::vector< double > fBoostWeights
std::map< TMVA::Event *, std::pair<
Double_t, Double_t > > 		fWeightedResiduals
std::map< TMVA::Event *, std::vector<
double > > 		fResiduals
SeparationBase * fSepType
TTree * fMonitorNtuple
std::vector< Double_t > fVariableImportance

Static Private Attributes

static const Int_t fgDebugLevel

Detailed Description

Definition at line 62 of file MethodBDT.h.

Constructor & Destructor Documentation

TMVA::MethodBDT::MethodBDT ( const TString &  jobName,
const TString &  methodTitle,
DataSetInfo &  theData,
const TString &  theOption = "",
TDirectory *  theTargetDir = 0 
)

TMVA::MethodBDT::MethodBDT ( DataSetInfo &  theData,
const TString &  theWeightFile,
TDirectory *  theTargetDir = NULL 
)

Definition at line 187 of file MethodBDT.cxx.

References fMonitorNtuple, fSepType, and NULL.

TMVA::MethodBDT::~MethodBDT ( void   )  [virtual]

Definition at line 516 of file MethodBDT.cxx.

References fEventSample, fForest, fValidationSample, and i.

TMVA::MethodBDT::MethodBDT ( const TString &  jobName,
const TString &  methodTitle,
DataSetInfo &  theData,
const TString &  theOption = "",
TDirectory *  theTargetDir = 0 
)

TMVA::MethodBDT::MethodBDT ( DataSetInfo &  theData,
const TString &  theWeightFile,
TDirectory *  theTargetDir = NULL 
)

virtual TMVA::MethodBDT::~MethodBDT ( void   )  [virtual]

Member Function Documentation

Bool_t TMVA::MethodBDT::HasAnalysisType ( Types::EAnalysisType  type,
UInt_t  numberClasses,
UInt_t  numberTargets 
) [virtual]

Implements TMVA::IMethod.

Definition at line 233 of file MethodBDT.cxx.

References TMVA::Types::kClassification, kFALSE, TMVA::Types::kMulticlass, TMVA::Types::kRegression, and kTRUE.

void TMVA::MethodBDT::InitEventSample (  ) 

Definition at line 525 of file MethodBDT.cxx.

References ceil(), TMVA::MethodBase::Data(), Endl, Event, fAutomatic, fEventSample, fFValidationEvents, floor(), fValidationSample, TMVA::DataSet::GetNTrainingEvents(), TMVA::MethodBase::GetTrainingEvent(), TMVA::MethodBase::HasTrainingTree(), TMVA::MethodBase::IgnoreEventsWithNegWeightsInTraining(), kFALSE, TMVA::kFATAL, TMVA::kINFO, kTRUE, TMVA::kWARNING, and TMVA::Configurable::Log().

Referenced by Train().

std::map< TString, Double_t > TMVA::MethodBDT::OptimizeTuningParameters ( TString  fomType = "ROCIntegral",
TString  fitType = "FitGA" 
) [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 578 of file MethodBDT.cxx.

References TMVA::MethodBase::Data(), Endl, TMVA::kINFO, TMVA::Configurable::Log(), max, TMath::Max(), min, TMath::Min(), N, and TMVA::OptimizeConfigParameters::optimize().

void TMVA::MethodBDT::SetTuneParameters ( std::map< TString, Double_t >  tuneParameters  )  [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 624 of file MethodBDT.cxx.

References SetAdaBoostBeta(), SetMaxDepth(), SetNodeMinEvents(), SetNodePurityLimit(), and SetNTrees().

void TMVA::MethodBDT::Train ( void   )  [virtual]

Implements TMVA::MethodBase.

Definition at line 640 of file MethodBDT.cxx.

References TTree::Branch(), TMVA::MethodBase::Data(), TMVA::MethodBase::DataInfo(), TMVA::MethodBase::DoMulticlass(), TMVA::MethodBase::DoRegression(), Endl, fAdaBoostBeta, fAutomatic, fBaggedGradBoost, fBoostType, fBoostWeight, fBoostWeights, fErrorFraction, fEventSample, fForest, TMVA::DecisionTreeNode::fgIsTraining, TTree::Fill(), fITree, fMaxDepth, fMinLinCorrForFisher, fMonitorNtuple, fNCuts, fNNodesMax, fNodeMinEvents, fNodePurityLimit, fNTrees, fPruneBeforeBoost, fPruneMethod, fPruneStrength, fRandomisedTrees, fSepType, fSubSample, fUseExclusiveVars, fUseFisherCuts, fUseNvars, fUsePoissonNvars, fUseYesNoLeaf, fValidationSample, TMVA::MethodBase::GetAnalysisType(), TMVA::MethodBase::GetMethodName(), TMVA::MethodBase::GetName(), TMVA::DataSetInfo::GetNClasses(), TMVA::DataSet::GetResults(), h, i, InitEventSample(), InitGradBoost(), TMVA::MethodBase::IsNormalised(), TMVA::kDEBUG, TMVA::kERROR, TMVA::kFATAL, TMVA::kINFO, TMVA::DecisionTree::kNoPruning, TMVA::Types::kTraining, TMVA::Configurable::Log(), NULL, TH1::SetBinContent(), TH1::SetXTitle(), TH1::SetYTitle(), TMVA::Results::Store(), and timer.

void TMVA::MethodBDT::Reset ( void   )  [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 492 of file MethodBDT.cxx.

References TMVA::MethodBase::Data(), TTree::Delete(), TMVA::DataSet::DeleteResults(), Endl, fBoostWeights, fForest, fMonitorNtuple, fResiduals, fVariableImportance, TMVA::MethodBase::GetAnalysisType(), TMVA::MethodBase::GetMethodName(), i, TMVA::kDEBUG, TMVA::Types::kTraining, TMVA::Configurable::Log(), and NULL.

void TMVA::MethodBDT::AddWeightsXMLTo ( void *  parent  )  const [virtual]

Implements TMVA::MethodBase.

Definition at line 1396 of file MethodBDT.cxx.

References TMVA::Tools::AddAttr(), TMVA::Tools::AddChild(), fBoostWeights, fForest, and TMVA::gTools().

void TMVA::MethodBDT::ReadWeightsFromStream ( istream &  istr  ) 

Definition at line 1444 of file MethodBDT.cxx.

References dummy, fBoostWeights, fForest, fNTrees, TMVA::MethodBase::GetTrainingTMVAVersionCode(), TMVA::kFATAL, TMVA::kINFO, and TMVA::Configurable::Log().

void TMVA::MethodBDT::ReadWeightsFromXML ( void *  parent  )  [virtual]

Implements TMVA::MethodBase.

Definition at line 1411 of file MethodBDT.cxx.

References TMVA::DecisionTree::CreateFromXML(), fBoostWeights, fForest, TMVA::Tools::GetChild(), TMVA::Tools::GetNextChild(), TMVA::MethodBase::GetTrainingTMVAVersionCode(), TMVA::gTools(), and TMVA::Tools::ReadAttr().

void TMVA::MethodBDT::WriteMonitoringHistosToFile ( void   )  const [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 1643 of file MethodBDT.cxx.

References TMVA::MethodBase::BaseDir(), fMonitorNtuple, TDirectory::GetPath(), TMVA::kINFO, TMVA::Configurable::Log(), and TTree::Write().

Double_t TMVA::MethodBDT::GetMvaValue ( Double_t *  err = 0,
Double_t *  errUpper = 0 
) [virtual]

Implements TMVA::MethodBase.

Definition at line 1479 of file MethodBDT.cxx.

Referenced by IsSignalLike().

Double_t TMVA::MethodBDT::GetMvaValue ( Double_t *  err,
Double_t *  errUpper,
UInt_t  useNTrees 
) [private]

Definition at line 1484 of file MethodBDT.cxx.

References CheckEvent(), RootCsg::epsilon, fBoostType, fBoostWeights, fForest, fUseWeightedTrees, fUseYesNoLeaf, TMVA::MethodBase::GetEvent(), GetGradBoostMVA(), and TMVA::MethodBase::NoErrorCalc().

const std::vector< Float_t > & TMVA::MethodBDT::GetMulticlassValues (  )  [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 1517 of file MethodBDT.cxx.

References CheckEvent(), TMVA::MethodBase::DataInfo(), exp(), fForest, TMVA::MethodBase::fMulticlassReturnVal, TMVA::MethodBase::GetEvent(), TMVA::DataSetInfo::GetNClasses(), j, kFALSE, and NULL.

const std::vector< Float_t > & TMVA::MethodBDT::GetRegressionValues (  )  [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 1552 of file MethodBDT.cxx.

References CheckEvent(), RootCsg::epsilon, Event, fBoostType, fBoostWeights, fForest, TMVA::MethodBase::fRegressionReturnVal, fUseWeightedTrees, TMVA::MethodBase::GetEvent(), TMVA::Event::GetTarget(), TMVA::MethodBase::GetTransformationHandler(), TMVA::gTools(), TMVA::TransformationHandler::InverseTransform(), kFALSE, TMath::Max(), TMath::Min(), NULL, TMVA::Event::SetTarget(), t, and TMVA::Tools::UsefulSortAscending().

Double_t TMVA::MethodBDT::Boost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt,
Int_t  iTree,
UInt_t  cls = 0 
)

const TMVA::Ranking * TMVA::MethodBDT::CreateRanking (  )  [virtual]

Implements TMVA::MethodBase.

Definition at line 1691 of file MethodBDT.cxx.

References TMVA::Ranking::AddRank(), TMVA::MethodBase::fRanking, TMVA::MethodBase::GetInputLabel(), TMVA::MethodBase::GetName(), and TMVA::MethodBase::GetNvar().

void TMVA::MethodBDT::DeclareOptions (  )  [virtual]

Implements TMVA::MethodBase.

Definition at line 243 of file MethodBDT.cxx.

References TMVA::Configurable::AddPreDefVal(), TMVA::Configurable::DeclareOptionRef(), TMVA::MethodBase::DoRegression(), fAdaBoostBeta, fAdaBoostR2Loss, fBaggedGradBoost, fBoostType, fFValidationEvents, fMaxDepth, fMinLinCorrForFisher, fNCuts, fNNodesMax, fNodeMinEvents, fNodePurityLimit, fNTrees, fPruneBeforeBoost, fPruneMethodS, fPruneStrength, fRandomisedTrees, fRenormByClass, fSampleFraction, fSepTypeS, fShrinkage, fUseExclusiveVars, fUseFisherCuts, fUseNTrainEvents, fUseNvars, fUsePoissonNvars, fUseWeightedTrees, fUseYesNoLeaf, kFALSE, and kTRUE.

void TMVA::MethodBDT::ProcessOptions (  )  [virtual]

Implements TMVA::MethodBase.

Definition at line 364 of file MethodBDT.cxx.

References TMVA::MethodBase::DoRegression(), Endl, fAdaBoostR2Loss, fAutomatic, fBaggedGradBoost, fBoostType, fFValidationEvents, fNodeMinEvents, fNTrees, fPruneMethod, fPruneMethodS, fPruneStrength, fRandomisedTrees, fSepType, fSepTypeS, fUseYesNoLeaf, TMVA::Configurable::GetOptions(), TMVA::MethodBase::IsConstructedFromWeightFile(), TMVA::DecisionTree::kCostComplexityPruning, TMVA::kERROR, TMVA::DecisionTree::kExpectedErrorPruning, kFALSE, TMVA::kFATAL, TMVA::kINFO, TMVA::DecisionTree::kNoPruning, kTRUE, TMVA::kWARNING, TMVA::Configurable::Log(), NULL, and TString::ToLower().

void TMVA::MethodBDT::SetMaxDepth ( Int_t  d  )  [inline]

Definition at line 129 of file MethodBDT.h.

References fMaxDepth.

Referenced by SetTuneParameters().

void TMVA::MethodBDT::SetNodeMinEvents ( Int_t  d  )  [inline]

Definition at line 130 of file MethodBDT.h.

References fNodeMinEvents.

Referenced by SetTuneParameters().

void TMVA::MethodBDT::SetNTrees ( Int_t  d  )  [inline]

Definition at line 131 of file MethodBDT.h.

References fNTrees.

Referenced by SetTuneParameters().

void TMVA::MethodBDT::SetAdaBoostBeta ( Double_t  b  )  [inline]

Definition at line 132 of file MethodBDT.h.

References fAdaBoostBeta.

Referenced by SetTuneParameters().

void TMVA::MethodBDT::SetNodePurityLimit ( Double_t  l  )  [inline]

Definition at line 133 of file MethodBDT.h.

References fNodePurityLimit.

Referenced by SetTuneParameters().

const std::vector< TMVA::DecisionTree * > & TMVA::MethodBDT::GetForest (  )  const [inline]

Definition at line 260 of file MethodBDT.h.

References fForest.

const std::vector< TMVA::Event * > & TMVA::MethodBDT::GetTrainingEvents (  )  const [inline]

Definition at line 261 of file MethodBDT.h.

References fEventSample.

const std::vector< double > & TMVA::MethodBDT::GetBoostWeights (  )  const [inline]

Definition at line 262 of file MethodBDT.h.

References fBoostWeights.

vector< Double_t > TMVA::MethodBDT::GetVariableImportance (  ) 

Definition at line 1655 of file MethodBDT.cxx.

References fForest, fNTrees, fVariableImportance, and TMVA::MethodBase::GetNvar().

Referenced by GetVariableImportance().

Double_t TMVA::MethodBDT::GetVariableImportance ( UInt_t  ivar  ) 

Definition at line 1677 of file MethodBDT.cxx.

References GetVariableImportance(), TMVA::kFATAL, and TMVA::Configurable::Log().

Double_t TMVA::MethodBDT::TestTreeQuality ( DecisionTree *  dt  ) 

Definition at line 1067 of file MethodBDT.cxx.

References TMVA::DecisionTree::CheckEvent(), TMVA::MethodBase::DataInfo(), fNodePurityLimit, and fValidationSample.

void TMVA::MethodBDT::MakeClassSpecific ( std::ostream &  ,
const TString &   
) const [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 1767 of file MethodBDT.cxx.

References fBoostType, fBoostWeights, fForest, fNTrees, fUseWeightedTrees, fUseYesNoLeaf, and MakeClassInstantiateNode().

void TMVA::MethodBDT::MakeClassSpecificHeader ( std::ostream &  ,
const TString &   
) const [virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 1829 of file MethodBDT.cxx.

void TMVA::MethodBDT::MakeClassInstantiateNode ( DecisionTreeNode *  n,
std::ostream &  fout,
const TString &  className 
) const

Definition at line 1908 of file MethodBDT.cxx.

References TMVA::kFATAL, TMVA::Configurable::Log(), n, and NULL.

Referenced by MakeClassSpecific().

void TMVA::MethodBDT::GetHelpMessage (  )  const [virtual]

Implements TMVA::IMethod.

Definition at line 1708 of file MethodBDT.cxx.

References TMVA::Tools::Color(), TMVA::gTools(), and TMVA::Configurable::Log().

virtual Bool_t TMVA::MethodBDT::IsSignalLike (  )  [inline, virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 161 of file MethodBDT.h.

References GetMvaValue().

void TMVA::MethodBDT::DeclareCompatibilityOptions (  )  [protected, virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 354 of file MethodBDT.cxx.

References TMVA::MethodBase::DeclareCompatibilityOptions(), TMVA::Configurable::DeclareOptionRef(), fNoNegWeightsInTraining, and fSampleSizeFraction.

void TMVA::MethodBDT::Init ( void   )  [private, virtual]

Implements TMVA::MethodBase.

Definition at line 451 of file MethodBDT.cxx.

References TMVA::MethodBase::Data(), TMVA::MethodBase::DataInfo(), fAdaBoostR2Loss, TMVA::MethodBase::fAnalysisType, fAutomatic, fBoostType, fFValidationEvents, fMaxDepth, fNCuts, fNNodesMax, fNodeMinEvents, fNTrees, fPruneMethod, fPruneMethodS, fPruneStrength, fRandomisedTrees, fShrinkage, fSumOfWeights, fUseNTrainEvents, fUseNvars, fUsePoissonNvars, TMVA::DataSet::GetNTrainingEvents(), TMVA::MethodBase::GetNvar(), TMVA::Types::kClassification, kFALSE, TMVA::Types::kMulticlass, TMVA::DecisionTree::kNoPruning, kTRUE, TMath::Max(), TMVA::MethodBase::SetSignalReferenceCut(), and TMath::Sqrt().

Double_t TMVA::MethodBDT::AdaBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::Bagging ( std::vector< TMVA::Event * >  ,
Int_t  iTree 
) [private]

Double_t TMVA::MethodBDT::RegBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::AdaBoostR2 ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::GradBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt,
UInt_t  cls = 0 
) [private]

Double_t TMVA::MethodBDT::GradBoostRegression ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

void TMVA::MethodBDT::InitGradBoost ( std::vector< TMVA::Event * >   )  [private]

Referenced by Train().

void TMVA::MethodBDT::UpdateTargets ( std::vector< TMVA::Event * >  ,
UInt_t  cls = 0 
) [private]

void TMVA::MethodBDT::UpdateTargetsRegression ( std::vector< TMVA::Event * >  ,
Bool_t  first = kFALSE 
) [private]

Double_t TMVA::MethodBDT::GetGradBoostMVA ( TMVA::Event &  e,
UInt_t  nTrees 
) [private]

Definition at line 861 of file MethodBDT.cxx.

References CheckEvent(), exp(), fForest, and kFALSE.

Referenced by GetMvaValue().

void TMVA::MethodBDT::GetRandomSubSample (  )  [private]

Definition at line 846 of file MethodBDT.cxx.

References fEventSample, fForest, fSampleFraction, fSubSample, and TRandom3::Rndm().

Double_t TMVA::MethodBDT::GetWeightedQuantile ( std::vector< std::pair< Double_t, Double_t > >  vec,
const Double_t  quantile,
const Double_t  SumOfWeights = 0.0 
) [private]

virtual Bool_t TMVA::MethodBDT::HasAnalysisType ( Types::EAnalysisType  type,
UInt_t  numberClasses,
UInt_t  numberTargets 
) [virtual]

Implements TMVA::IMethod.

void TMVA::MethodBDT::InitEventSample (  ) 

virtual std::map<TString,Double_t> TMVA::MethodBDT::OptimizeTuningParameters ( TString  fomType = "ROCIntegral",
TString  fitType = "FitGA" 
) [virtual]

Reimplemented from TMVA::MethodBase.

virtual void TMVA::MethodBDT::SetTuneParameters ( std::map< TString, Double_t >  tuneParameters  )  [virtual]

Reimplemented from TMVA::MethodBase.

void TMVA::MethodBDT::Train ( void   )  [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::Reset ( void   )  [virtual]

Reimplemented from TMVA::MethodBase.

void TMVA::MethodBDT::AddWeightsXMLTo ( void *  parent  )  const [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::ReadWeightsFromStream ( istream &  istr  ) 

void TMVA::MethodBDT::ReadWeightsFromXML ( void *  parent  )  [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::WriteMonitoringHistosToFile ( void   )  const [virtual]

Reimplemented from TMVA::MethodBase.

Double_t TMVA::MethodBDT::GetMvaValue ( Double_t *  err = 0,
Double_t *  errUpper = 0 
) [virtual]

Implements TMVA::MethodBase.

Double_t TMVA::MethodBDT::GetMvaValue ( Double_t *  err,
Double_t *  errUpper,
UInt_t  useNTrees 
) [private]

const std::vector<Float_t>& TMVA::MethodBDT::GetMulticlassValues (  )  [virtual]

Reimplemented from TMVA::MethodBase.

const std::vector<Float_t>& TMVA::MethodBDT::GetRegressionValues (  )  [virtual]

Reimplemented from TMVA::MethodBase.

Double_t TMVA::MethodBDT::Boost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt,
Int_t  iTree,
UInt_t  cls = 0 
)

const Ranking* TMVA::MethodBDT::CreateRanking (  )  [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::DeclareOptions (  )  [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::ProcessOptions (  )  [virtual]

Implements TMVA::MethodBase.

void TMVA::MethodBDT::SetMaxDepth ( Int_t  d  )  [inline]

Definition at line 129 of file MethodBDT.h.

References fMaxDepth.

void TMVA::MethodBDT::SetNodeMinEvents ( Int_t  d  )  [inline]

Definition at line 130 of file MethodBDT.h.

References fNodeMinEvents.

void TMVA::MethodBDT::SetNTrees ( Int_t  d  )  [inline]

Definition at line 131 of file MethodBDT.h.

References fNTrees.

void TMVA::MethodBDT::SetAdaBoostBeta ( Double_t  b  )  [inline]

Definition at line 132 of file MethodBDT.h.

References fAdaBoostBeta.

void TMVA::MethodBDT::SetNodePurityLimit ( Double_t  l  )  [inline]

Definition at line 133 of file MethodBDT.h.

References fNodePurityLimit.

const std::vector<TMVA::DecisionTree*>& TMVA::MethodBDT::GetForest (  )  const [inline]

const std::vector<TMVA::Event*>& TMVA::MethodBDT::GetTrainingEvents (  )  const [inline]

const std::vector<double>& TMVA::MethodBDT::GetBoostWeights (  )  const [inline]

std::vector<Double_t> TMVA::MethodBDT::GetVariableImportance (  ) 

Double_t TMVA::MethodBDT::GetVariableImportance ( UInt_t  ivar  ) 

Double_t TMVA::MethodBDT::TestTreeQuality ( DecisionTree *  dt  ) 

void TMVA::MethodBDT::MakeClassSpecific ( std::ostream &  ,
const TString &   
) const [virtual]

Reimplemented from TMVA::MethodBase.

void TMVA::MethodBDT::MakeClassSpecificHeader ( std::ostream &  ,
const TString &   
) const [virtual]

Reimplemented from TMVA::MethodBase.

void TMVA::MethodBDT::MakeClassInstantiateNode ( DecisionTreeNode *  n,
std::ostream &  fout,
const TString &  className 
) const

void TMVA::MethodBDT::GetHelpMessage (  )  const [virtual]

Implements TMVA::IMethod.

virtual Bool_t TMVA::MethodBDT::IsSignalLike (  )  [inline, virtual]

Reimplemented from TMVA::MethodBase.

Definition at line 161 of file MethodBDT.h.

References GetMvaValue().

void TMVA::MethodBDT::DeclareCompatibilityOptions (  )  [protected, virtual]

Reimplemented from TMVA::MethodBase.

void TMVA::MethodBDT::Init ( void   )  [private, virtual]

Implements TMVA::MethodBase.

Double_t TMVA::MethodBDT::AdaBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::Bagging ( std::vector< TMVA::Event * >  ,
Int_t  iTree 
) [private]

Double_t TMVA::MethodBDT::RegBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::AdaBoostR2 ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

Double_t TMVA::MethodBDT::GradBoost ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt,
UInt_t  cls = 0 
) [private]

Double_t TMVA::MethodBDT::GradBoostRegression ( std::vector< TMVA::Event * >  ,
DecisionTree *  dt 
) [private]

void TMVA::MethodBDT::InitGradBoost ( std::vector< TMVA::Event * >   )  [private]

void TMVA::MethodBDT::UpdateTargets ( std::vector< TMVA::Event * >  ,
UInt_t  cls = 0 
) [private]

void TMVA::MethodBDT::UpdateTargetsRegression ( std::vector< TMVA::Event * >  ,
Bool_t  first = kFALSE 
) [private]

Double_t TMVA::MethodBDT::GetGradBoostMVA ( TMVA::Event &  e,
UInt_t  nTrees 
) [private]

void TMVA::MethodBDT::GetRandomSubSample (  )  [private]

Double_t TMVA::MethodBDT::GetWeightedQuantile ( std::vector< std::pair< Double_t, Double_t > >  vec,
const Double_t  quantile,
const Double_t  SumOfWeights = 0.0 
) [private]

Member Data Documentation

std::vector<TMVA::Event*> TMVA::MethodBDT::fEventSample [private]

Definition at line 193 of file MethodBDT.h.

Referenced by GetRandomSubSample(), GetTrainingEvents(), InitEventSample(), Train(), and ~MethodBDT().

std::vector<TMVA::Event*> TMVA::MethodBDT::fValidationSample [private]

Definition at line 194 of file MethodBDT.h.

Referenced by InitEventSample(), TestTreeQuality(), Train(), and ~MethodBDT().

std::vector<TMVA::Event*> TMVA::MethodBDT::fSubSample [private]

Definition at line 195 of file MethodBDT.h.

Referenced by GetRandomSubSample(), and Train().

Int_t TMVA::MethodBDT::fNTrees [private]

Definition at line 196 of file MethodBDT.h.

Referenced by DeclareOptions(), GetVariableImportance(), Init(), MakeClassSpecific(), ProcessOptions(), ReadWeightsFromStream(), SetNTrees(), and Train().

std::vector<DecisionTree*> TMVA::MethodBDT::fForest [private]

Definition at line 197 of file MethodBDT.h.

Referenced by AddWeightsXMLTo(), GetForest(), GetGradBoostMVA(), GetMulticlassValues(), GetMvaValue(), GetRandomSubSample(), GetRegressionValues(), GetVariableImportance(), MakeClassSpecific(), ReadWeightsFromStream(), ReadWeightsFromXML(), Reset(), Train(), and ~MethodBDT().

std::vector<double> TMVA::MethodBDT::fBoostWeights [private]

Definition at line 198 of file MethodBDT.h.

Referenced by AddWeightsXMLTo(), GetBoostWeights(), GetMvaValue(), GetRegressionValues(), MakeClassSpecific(), ReadWeightsFromStream(), ReadWeightsFromXML(), Reset(), and Train().

Bool_t TMVA::MethodBDT::fRenormByClass [private]

Definition at line 199 of file MethodBDT.h.

Referenced by DeclareOptions().

TString TMVA::MethodBDT::fBoostType [private]

Definition at line 200 of file MethodBDT.h.

Referenced by DeclareOptions(), GetMvaValue(), GetRegressionValues(), Init(), MakeClassSpecific(), ProcessOptions(), and Train().

Double_t TMVA::MethodBDT::fAdaBoostBeta [private]

Definition at line 201 of file MethodBDT.h.

Referenced by DeclareOptions(), SetAdaBoostBeta(), and Train().

TString TMVA::MethodBDT::fAdaBoostR2Loss [private]

Definition at line 202 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and ProcessOptions().

Double_t TMVA::MethodBDT::fTransitionPoint [private]

Definition at line 203 of file MethodBDT.h.

Double_t TMVA::MethodBDT::fShrinkage [private]

Definition at line 204 of file MethodBDT.h.

Referenced by DeclareOptions(), and Init().

Bool_t TMVA::MethodBDT::fBaggedGradBoost [private]

Definition at line 205 of file MethodBDT.h.

Referenced by DeclareOptions(), ProcessOptions(), and Train().

Double_t TMVA::MethodBDT::fSampleFraction [private]

Definition at line 206 of file MethodBDT.h.

Referenced by DeclareOptions(), and GetRandomSubSample().

Double_t TMVA::MethodBDT::fSumOfWeights [private]

Definition at line 207 of file MethodBDT.h.

Referenced by Init().

std::map< TMVA::Event*, std::pair<Double_t, Double_t> > TMVA::MethodBDT::fWeightedResiduals [private]

Definition at line 208 of file MethodBDT.h.

std::map< TMVA::Event*,std::vector<double> > TMVA::MethodBDT::fResiduals [private]

Definition at line 209 of file MethodBDT.h.

Referenced by Reset().

SeparationBase* TMVA::MethodBDT::fSepType [private]

Definition at line 212 of file MethodBDT.h.

Referenced by MethodBDT(), ProcessOptions(), and Train().

TString TMVA::MethodBDT::fSepTypeS [private]

Definition at line 213 of file MethodBDT.h.

Referenced by DeclareOptions(), and ProcessOptions().

Int_t TMVA::MethodBDT::fNodeMinEvents [private]

Definition at line 214 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), ProcessOptions(), SetNodeMinEvents(), and Train().

Int_t TMVA::MethodBDT::fNCuts [private]

Definition at line 216 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and Train().

Bool_t TMVA::MethodBDT::fUseFisherCuts [private]

Definition at line 217 of file MethodBDT.h.

Referenced by DeclareOptions(), and Train().

Double_t TMVA::MethodBDT::fMinLinCorrForFisher [private]

Definition at line 218 of file MethodBDT.h.

Referenced by DeclareOptions(), and Train().

Bool_t TMVA::MethodBDT::fUseExclusiveVars [private]

Definition at line 219 of file MethodBDT.h.

Referenced by DeclareOptions(), and Train().

Bool_t TMVA::MethodBDT::fUseYesNoLeaf [private]

Definition at line 220 of file MethodBDT.h.

Referenced by DeclareOptions(), GetMvaValue(), MakeClassSpecific(), ProcessOptions(), and Train().

Double_t TMVA::MethodBDT::fNodePurityLimit [private]

Definition at line 221 of file MethodBDT.h.

Referenced by DeclareOptions(), SetNodePurityLimit(), TestTreeQuality(), and Train().

Bool_t TMVA::MethodBDT::fUseWeightedTrees [private]

Definition at line 222 of file MethodBDT.h.

Referenced by DeclareOptions(), GetMvaValue(), GetRegressionValues(), and MakeClassSpecific().

UInt_t TMVA::MethodBDT::fNNodesMax [private]

Definition at line 223 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and Train().

UInt_t TMVA::MethodBDT::fMaxDepth [private]

Definition at line 224 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), SetMaxDepth(), and Train().

DecisionTree::EPruneMethod TMVA::MethodBDT::fPruneMethod [private]

Definition at line 226 of file MethodBDT.h.

Referenced by Init(), ProcessOptions(), and Train().

TString TMVA::MethodBDT::fPruneMethodS [private]

Definition at line 227 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and ProcessOptions().

Double_t TMVA::MethodBDT::fPruneStrength [private]

Definition at line 228 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), ProcessOptions(), and Train().

Bool_t TMVA::MethodBDT::fPruneBeforeBoost [private]

Definition at line 229 of file MethodBDT.h.

Referenced by DeclareOptions(), and Train().

Double_t TMVA::MethodBDT::fFValidationEvents [private]

Definition at line 230 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), InitEventSample(), and ProcessOptions().

Bool_t TMVA::MethodBDT::fAutomatic [private]

Definition at line 231 of file MethodBDT.h.

Referenced by Init(), InitEventSample(), ProcessOptions(), and Train().

Bool_t TMVA::MethodBDT::fRandomisedTrees [private]

Definition at line 232 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), ProcessOptions(), and Train().

UInt_t TMVA::MethodBDT::fUseNvars [private]

Definition at line 233 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and Train().

Bool_t TMVA::MethodBDT::fUsePoissonNvars [private]

Definition at line 234 of file MethodBDT.h.

Referenced by DeclareOptions(), Init(), and Train().

UInt_t TMVA::MethodBDT::fUseNTrainEvents [private]

Definition at line 235 of file MethodBDT.h.

Referenced by DeclareOptions(), and Init().

Double_t TMVA::MethodBDT::fSampleSizeFraction [private]

Definition at line 237 of file MethodBDT.h.

Referenced by DeclareCompatibilityOptions().

Bool_t TMVA::MethodBDT::fNoNegWeightsInTraining [private]

Definition at line 238 of file MethodBDT.h.

Referenced by DeclareCompatibilityOptions().

TTree* TMVA::MethodBDT::fMonitorNtuple [private]

Definition at line 243 of file MethodBDT.h.

Referenced by MethodBDT(), Reset(), Train(), and WriteMonitoringHistosToFile().

Int_t TMVA::MethodBDT::fITree [private]

Definition at line 244 of file MethodBDT.h.

Referenced by Train().

Double_t TMVA::MethodBDT::fBoostWeight [private]

Definition at line 245 of file MethodBDT.h.

Referenced by Train().

Double_t TMVA::MethodBDT::fErrorFraction [private]

Definition at line 246 of file MethodBDT.h.

Referenced by Train().

std::vector<Double_t> TMVA::MethodBDT::fVariableImportance [private]

Definition at line 248 of file MethodBDT.h.

Referenced by GetVariableImportance(), and Reset().

static const Int_t TMVA::MethodBDT::fgDebugLevel [static, private]

Definition at line 251 of file MethodBDT.h.

std::vector<TMVA::Event*> TMVA::MethodBDT::fEventSample [private]

Definition at line 193 of file MethodBDT.h.

std::vector<TMVA::Event*> TMVA::MethodBDT::fValidationSample [private]

Definition at line 194 of file MethodBDT.h.

std::vector<TMVA::Event*> TMVA::MethodBDT::fSubSample [private]

Definition at line 195 of file MethodBDT.h.

std::vector<DecisionTree*> TMVA::MethodBDT::fForest [private]

Definition at line 197 of file MethodBDT.h.

std::vector<double> TMVA::MethodBDT::fBoostWeights [private]

Definition at line 198 of file MethodBDT.h.

std::map< TMVA::Event*, std::pair<Double_t, Double_t> > TMVA::MethodBDT::fWeightedResiduals [private]

Definition at line 208 of file MethodBDT.h.

std::map< TMVA::Event*,std::vector<double> > TMVA::MethodBDT::fResiduals [private]

Definition at line 209 of file MethodBDT.h.

SeparationBase* TMVA::MethodBDT::fSepType [private]

Definition at line 212 of file MethodBDT.h.

TTree* TMVA::MethodBDT::fMonitorNtuple [private]

Definition at line 243 of file MethodBDT.h.

std::vector<Double_t> TMVA::MethodBDT::fVariableImportance [private]

Definition at line 248 of file MethodBDT.h.

The documentation for this class was generated from the following files:
Generated on Tue Jul 5 17:01:27 2011 for ROOT_528-00b_version by  doxygen 1.5.1