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class TMVA::MethodBoost: public TMVA::MethodCompositeBase


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

Function Members (Methods)

public:
virtual~MethodBoost()
voidTObject::AbstractMethod(const char* method) const
voidTMVA::Configurable::AddOptionsXMLTo(void* parent) const
voidTMVA::MethodBase::AddOutput(TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysisType)
virtual voidTMVA::MethodCompositeBase::AddWeightsXMLTo(void* parent) const
virtual voidTObject::AppendPad(Option_t* option = "")
TDirectory*TMVA::MethodBase::BaseDir() const
Bool_tBookMethod(TMVA::Types::EMVA theMethod, TString methodTitle, TString theOption)
virtual voidTObject::Browse(TBrowser* b)
voidTMVA::Configurable::CheckForUnusedOptions() const
static TClass*Class()
virtual const char*TObject::ClassName() const
voidCleanBoostOptions()
virtual voidTObject::Clear(Option_t* = "")
virtual TObject*TObject::Clone(const char* newname = "") const
virtual Int_tTObject::Compare(const TObject* obj) const
TMVA::ConfigurableTMVA::Configurable::Configurable(const TString& theOption = "")
virtual voidTObject::Copy(TObject& object) const
virtual const TMVA::Ranking*CreateRanking()
TMVA::DataSet*TMVA::MethodBase::Data() const
TMVA::DataSetInfo&TMVA::MethodBase::DataInfo() const
virtual voidTObject::Delete(Option_t* option = "")MENU
voidTMVA::MethodBase::DisableWriting(Bool_t setter)
virtual Int_tTObject::DistancetoPrimitive(Int_t px, Int_t py)
Bool_tTMVA::MethodBase::DoMulticlass() const
Bool_tTMVA::MethodBase::DoRegression() const
virtual voidTObject::Draw(Option_t* option = "")
virtual voidTObject::DrawClass() constMENU
virtual TObject*TObject::DrawClone(Option_t* option = "") constMENU
virtual voidTObject::Dump() constMENU
virtual voidTObject::Error(const char* method, const char* msgfmt) const
virtual voidTObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual voidTObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual voidTObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual TObject*TObject::FindObject(const char* name) const
virtual TObject*TObject::FindObject(const TObject* obj) const
TMVA::Types::EAnalysisTypeTMVA::MethodBase::GetAnalysisType() const
Int_tGetBoostNum()
const char*TMVA::Configurable::GetConfigDescription() const
const char*TMVA::Configurable::GetConfigName() const
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
virtual Double_tTMVA::MethodBase::GetEfficiency(const TString&, TMVA::Types::ETreeType, Double_t& err)
const TMVA::Event*TMVA::MethodBase::GetEvent() const
const TMVA::Event*TMVA::MethodBase::GetEvent(const TMVA::Event* ev) const
const TMVA::Event*TMVA::MethodBase::GetEvent(Long64_t ievt) const
const TMVA::Event*TMVA::MethodBase::GetEvent(Long64_t ievt, TMVA::Types::ETreeType type) const
const vector<TMVA::Event*>&TMVA::MethodBase::GetEventCollection(TMVA::Types::ETreeType type)
virtual const char*TObject::GetIconName() const
const TString&TMVA::MethodBase::GetInputLabel(Int_t i) const
const TString&TMVA::MethodBase::GetInputTitle(Int_t i) const
const TString&TMVA::MethodBase::GetInputVar(Int_t i) const
const TString&TMVA::MethodBase::GetJobName() const
virtual Double_tTMVA::MethodBase::GetKSTrainingVsTest(Char_t SorB, TString opt = "X")
virtual Double_tTMVA::MethodBase::GetMaximumSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const
Double_tTMVA::MethodBase::GetMean(Int_t ivar) const
const TString&TMVA::MethodBase::GetMethodName() const
TMVA::Types::EMVATMVA::MethodBase::GetMethodType() const
TStringTMVA::MethodBase::GetMethodTypeName() const
virtual vector<Float_t>TMVA::MethodBase::GetMulticlassEfficiency(vector<std::vector<Float_t> >& purity)
virtual vector<Float_t>TMVA::MethodBase::GetMulticlassTrainingEfficiency(vector<std::vector<Float_t> >& purity)
virtual const vector<Float_t>&TMVA::MethodBase::GetMulticlassValues()
virtual Double_tGetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)
virtual const char*TMVA::MethodBase::GetName() const
UInt_tTMVA::MethodBase::GetNEvents() const
UInt_tTMVA::MethodBase::GetNTargets() const
UInt_tTMVA::MethodBase::GetNvar() const
UInt_tTMVA::MethodBase::GetNVariables() const
virtual char*TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Option_t*TObject::GetOption() const
const TString&TMVA::Configurable::GetOptions() const
virtual Double_tTMVA::MethodBase::GetProba(const TMVA::Event* ev)
virtual Double_tTMVA::MethodBase::GetProba(Double_t mvaVal, Double_t ap_sig)
const TStringTMVA::MethodBase::GetProbaName() const
virtual Double_tTMVA::MethodBase::GetRarity(Double_t mvaVal, TMVA::Types::ESBType reftype = Types::kBackground) const
virtual voidTMVA::MethodBase::GetRegressionDeviation(UInt_t tgtNum, TMVA::Types::ETreeType type, Double_t& stddev, Double_t& stddev90Percent) const
virtual const vector<Float_t>&TMVA::MethodBase::GetRegressionValues()
const vector<Float_t>&TMVA::MethodBase::GetRegressionValues(const TMVA::Event *const ev)
Double_tTMVA::MethodBase::GetRMS(Int_t ivar) const
virtual Double_tTMVA::MethodBase::GetROCIntegral(TH1D* histS, TH1D* histB) const
virtual Double_tTMVA::MethodBase::GetROCIntegral(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
virtual Double_tTMVA::MethodBase::GetSeparation(TH1*, TH1*) const
virtual Double_tTMVA::MethodBase::GetSeparation(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
Double_tTMVA::MethodBase::GetSignalReferenceCut() const
Double_tTMVA::MethodBase::GetSignalReferenceCutOrientation() const
virtual Double_tTMVA::MethodBase::GetSignificance() const
const TMVA::Event*TMVA::MethodBase::GetTestingEvent(Long64_t ievt) const
Double_tTMVA::MethodBase::GetTestTime() const
const TString&TMVA::MethodBase::GetTestvarName() const
virtual const char*TObject::GetTitle() const
virtual Double_tTMVA::MethodBase::GetTrainingEfficiency(const TString&)
const TMVA::Event*TMVA::MethodBase::GetTrainingEvent(Long64_t ievt) const
UInt_tTMVA::MethodBase::GetTrainingROOTVersionCode() const
TStringTMVA::MethodBase::GetTrainingROOTVersionString() const
UInt_tTMVA::MethodBase::GetTrainingTMVAVersionCode() const
TStringTMVA::MethodBase::GetTrainingTMVAVersionString() const
Double_tTMVA::MethodBase::GetTrainTime() const
TMVA::TransformationHandler&TMVA::MethodBase::GetTransformationHandler(Bool_t takeReroutedIfAvailable = true)
const TMVA::TransformationHandler&TMVA::MethodBase::GetTransformationHandler(Bool_t takeReroutedIfAvailable = true) const
virtual UInt_tTObject::GetUniqueID() const
TStringTMVA::MethodBase::GetWeightFileName() const
Double_tTMVA::MethodBase::GetXmax(Int_t ivar) const
Double_tTMVA::MethodBase::GetXmin(Int_t ivar) const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
virtual Bool_tHasAnalysisType(TMVA::Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
virtual ULong_tTObject::Hash() const
Bool_tTMVA::MethodBase::HasMVAPdfs() const
virtual voidTObject::Info(const char* method, const char* msgfmt) const
virtual Bool_tTObject::InheritsFrom(const char* classname) const
virtual Bool_tTObject::InheritsFrom(const TClass* cl) const
virtual voidTObject::Inspect() constMENU
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
Bool_tTObject::IsOnHeap() const
virtual Bool_tTMVA::MethodBase::IsSignalLike()
virtual Bool_tTMVA::MethodBase::IsSignalLike(Double_t mvaVal)
virtual Bool_tTObject::IsSortable() const
Bool_tTObject::IsZombie() const
virtual voidTObject::ls(Option_t* option = "") const
virtual voidTMVA::MethodBase::MakeClass(const TString& classFileName = TString("")) const
voidTObject::MayNotUse(const char* method) const
TDirectory*TMVA::MethodBase::MethodBaseDir() const
TMVA::MethodBoostMethodBoost(TMVA::DataSetInfo& dsi, const TString& theWeightFile, TDirectory* theTargetDir = NULL)
TMVA::MethodBoostMethodBoost(const TString& jobName, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption = "", TDirectory* theTargetDir = NULL)
virtual Bool_tTObject::Notify()
voidTObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
static voidTObject::operator delete(void* ptr)
static voidTObject::operator delete(void* ptr, void* vp)
static voidTObject::operator delete[](void* ptr)
static voidTObject::operator delete[](void* ptr, void* vp)
void*TObject::operator new(size_t sz)
void*TObject::operator new(size_t sz, void* vp)
void*TObject::operator new[](size_t sz)
void*TObject::operator new[](size_t sz, void* vp)
TMVA::IMethod&TMVA::IMethod::operator=(const TMVA::IMethod&)
virtual map<TString,Double_t>TMVA::MethodBase::OptimizeTuningParameters(TString fomType = "ROCIntegral", TString fitType = "FitGA")
virtual voidTObject::Paint(Option_t* option = "")
virtual voidTMVA::Configurable::ParseOptions()
virtual voidTObject::Pop()
virtual voidTObject::Print(Option_t* option = "") const
virtual voidTMVA::MethodBase::PrintHelpMessage() const
voidTMVA::Configurable::PrintOptions() const
voidTMVA::MethodBase::ProcessSetup()
virtual Int_tTObject::Read(const char* name)
voidTMVA::Configurable::ReadOptionsFromStream(istream& istr)
voidTMVA::Configurable::ReadOptionsFromXML(void* node)
voidTMVA::MethodBase::ReadStateFromFile()
voidTMVA::MethodBase::ReadStateFromStream(istream& tf)
voidTMVA::MethodBase::ReadStateFromStream(TFile& rf)
voidTMVA::MethodBase::ReadStateFromXMLString(const char* xmlstr)
virtual voidTMVA::MethodCompositeBase::ReadWeightsFromStream(istream& istr)
virtual voidTMVA::MethodCompositeBase::ReadWeightsFromXML(void* wghtnode)
virtual voidTObject::RecursiveRemove(TObject* obj)
voidTMVA::MethodBase::RerouteTransformationHandler(TMVA::TransformationHandler* fTargetTransformation)
virtual voidTMVA::MethodBase::Reset()
voidTObject::ResetBit(UInt_t f)
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual voidTObject::SavePrimitive(ostream& out, Option_t* option = "")
virtual voidTMVA::MethodBase::SetAnalysisType(TMVA::Types::EAnalysisType type)
voidTMVA::MethodBase::SetBaseDir(TDirectory* methodDir)
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
voidSetBoostedMethodName(TString methodName)
voidTMVA::Configurable::SetConfigDescription(const char* d)
voidTMVA::Configurable::SetConfigName(const char* n)
virtual voidTObject::SetDrawOption(Option_t* option = "")MENU
static voidTObject::SetDtorOnly(void* obj)
voidTMVA::MethodBase::SetMethodBaseDir(TDirectory* methodDir)
voidTMVA::MethodBase::SetMethodDir(TDirectory* methodDir)
voidTMVA::Configurable::SetMsgType(TMVA::EMsgType t)
static voidTObject::SetObjectStat(Bool_t stat)
voidTMVA::Configurable::SetOptions(const TString& s)
voidTMVA::MethodBase::SetSignalReferenceCut(Double_t cut)
voidTMVA::MethodBase::SetSignalReferenceCutOrientation(Double_t cutOrientation)
voidTMVA::MethodBase::SetTestTime(Double_t testTime)
voidTMVA::MethodBase::SetTestvarName(const TString& v = "")
voidTMVA::MethodBase::SetTrainTime(Double_t trainTime)
virtual voidTMVA::MethodBase::SetTuneParameters(map<TString,Double_t> tuneParameters)
virtual voidTObject::SetUniqueID(UInt_t uid)
voidTMVA::MethodBase::SetupMethod()
virtual voidShowMembers(TMemberInspector&)
virtual voidStreamer(TBuffer&)
voidStreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
virtual voidTMVA::MethodBase::TestMulticlass()
virtual voidTMVA::MethodBase::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, TMVA::Types::ETreeType type)
virtual voidTrain()
voidTMVA::MethodBase::TrainMethod()
virtual voidTObject::UseCurrentStyle()
virtual voidTObject::Warning(const char* method, const char* msgfmt) const
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const
voidTMVA::Configurable::WriteOptionsToStream(ostream& o, const TString& prefix) const
voidTMVA::MethodBase::WriteStateToFile() const
protected:
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const
voidTMVA::Configurable::EnableLooseOptions(Bool_t b = kTRUE)
TMVA::MethodBase*TMVA::MethodCompositeBase::GetCurrentMethod()
TMVA::MethodBase*TMVA::MethodCompositeBase::GetCurrentMethod(UInt_t idx)
UInt_tTMVA::MethodCompositeBase::GetCurrentMethodIndex()
virtual voidGetHelpMessage() const
const TString&TMVA::MethodBase::GetInternalVarName(Int_t ivar) const
TMVA::IMethod*TMVA::MethodCompositeBase::GetLastMethod()
TMVA::IMethod*TMVA::MethodCompositeBase::GetMethod(const TString& title) const
TMVA::IMethod*TMVA::MethodCompositeBase::GetMethod(const Int_t index) const
const TString&TMVA::MethodBase::GetOriginalVarName(Int_t ivar) const
TMVA::IMethod*TMVA::MethodCompositeBase::GetPreviousMethod()
const TString&TMVA::Configurable::GetReferenceFile() const
static TMVA::MethodBase*TMVA::MethodBase::GetThisBase()
const TString&TMVA::MethodBase::GetWeightFileDir() const
Bool_tTMVA::MethodBase::HasTrainingTree() const
Bool_tTMVA::MethodBase::Help() const
Bool_tTMVA::MethodBase::IgnoreEventsWithNegWeightsInTraining() const
Bool_tTMVA::MethodBase::IsConstructedFromWeightFile() const
Bool_tTMVA::MethodBase::IsNormalised() const
TMVA::MsgLogger&TMVA::Configurable::Log() const
Bool_tTMVA::Configurable::LooseOptionCheckingEnabled() const
virtual voidTMVA::MethodBase::MakeClassSpecific(ostream&, const TString& = "") const
virtual voidTMVA::MethodBase::MakeClassSpecificHeader(ostream&, const TString& = "") const
voidTObject::MakeZombie()
voidTMVA::MethodBase::NoErrorCalc(Double_t *const err, Double_t *const errUpper)
voidTMVA::Configurable::ResetSetFlag()
voidTMVA::MethodBase::SetNormalised(Bool_t norm)
voidTMVA::MethodBase::SetWeightFileDir(TString fileDir)
voidTMVA::MethodBase::SetWeightFileName(TString)
voidTMVA::MethodBase::Statistics(TMVA::Types::ETreeType treeType, const TString& theVarName, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&)
Bool_tTMVA::MethodBase::TxtWeightsOnly() const
Bool_tTMVA::MethodBase::Verbose() const
voidTMVA::Configurable::WriteOptionsReferenceToFile()
private:
Double_tAdaBoost(TMVA::MethodBase* method, Bool_t useYesNoLeaf)
Double_tBagging()
Double_tCalcMethodWeight()
voidCalcMVAValues()
virtual voidCheckSetup()
voidClearAll()
voidCreateMVAHistorgrams()
TMVA::MethodBase*CurrentMethod()
UInt_tCurrentMethodIdx()
virtual voidDeclareCompatibilityOptions()
virtual voidDeclareOptions()
voidFindMVACut(TMVA::MethodBase* method)
Double_tGetBoostROCIntegral(Bool_t, TMVA::Types::ETreeType, Bool_t CalcOverlapIntergral = kFALSE)
virtual voidInit()
voidInitHistos()
voidMonitorBoost(TMVA::Types::EBoostStage stage, UInt_t methodIdx = 0)
voidPrintResults(const TString&, vector<Double_t>&, const Double_t) const
virtual voidProcessOptions()
voidResetBoostWeights()
Double_tSingleBoost(TMVA::MethodBase* method)
voidSingleTrain()
virtual voidTestClassification()
virtual voidWriteEvaluationHistosToFile(TMVA::Types::ETreeType treetype)
virtual voidWriteMonitoringHistosToFile() const

Data Members

public:
enum TMVA::MethodBase::EWeightFileType { kROOT
kTEXT
};
enum TObject::EStatusBits { kCanDelete
kMustCleanup
kObjInCanvas
kIsReferenced
kHasUUID
kCannotPick
kNoContextMenu
kInvalidObject
};
enum TObject::[unnamed] { kIsOnHeap
kNotDeleted
kZombie
kBitMask
kSingleKey
kOverwrite
kWriteDelete
};
public:
Bool_tTMVA::MethodBase::fSetupCompletedis method setup
const TMVA::Event*TMVA::MethodBase::fTmpEvent! temporary event when testing on a different DataSet than the own one
protected:
TMVA::Types::EAnalysisTypeTMVA::MethodBase::fAnalysisTypemethod-mode : true --> regression, false --> classification
UInt_tTMVA::MethodBase::fBackgroundClassindex of the Background-class
TMVA::MethodBase*TMVA::MethodCompositeBase::fCurrentMethod
UInt_tTMVA::MethodCompositeBase::fCurrentMethodIdx
vector<TString>*TMVA::MethodBase::fInputVarsvector of input variables used in MVA
vector<Double_t>TMVA::MethodCompositeBase::fMethodWeight
vector<IMethod*>TMVA::MethodCompositeBase::fMethodsvector of all classifiers
vector<Float_t>*TMVA::MethodBase::fMulticlassReturnValholds the return-values for the multiclass classification
Int_tTMVA::MethodBase::fNbinsnumber of bins in input variable histograms
Int_tTMVA::MethodBase::fNbinsHnumber of bins in evaluation histograms
Int_tTMVA::MethodBase::fNbinsMVAoutputnumber of bins in MVA output histograms
TMVA::Ranking*TMVA::MethodBase::fRankingpointer to ranking object (created by derived classifiers)
vector<Float_t>*TMVA::MethodBase::fRegressionReturnValholds the return-values for the regression
UInt_tTMVA::MethodBase::fSignalClassindex of the Signal-class
private:
Double_tfAdaBoostBetaADA boost parameter, default is 1
vector<TH1*>fBTrainBgdMVAHist
vector<TH1*>fBTrainSigMVAHist
Double_tfBaggedSampleFractionrel.Size of bagged sample
UInt_tfBoostNumNumber of times the classifier is boosted
TStringfBoostTypestring specifying the boost type
Double_tfBoostWeightthe weight used to boost the next classifier
TStringfBoostedMethodNamedetails of the boosted classifier
TStringfBoostedMethodOptionsoptions
TStringfBoostedMethodTitletitle
TMVA::DataSetManager*fDataSetManagerDSMTEST
Bool_tfDetailedMonitoringproduce detailed monitoring histograms (boost-wise)
Bool_tfHistoricBoolOptionhistoric variable, only needed for "CompatibilityOptions"
TStringfHistoricOptionhistoric variable, only needed for "CompatibilityOptions"
vector<Float_t>*fMVAvaluesmva values for the last trained method
Double_tfMethodErrorestimation of the level error of the classifier
Bool_tfMonitorBoostedMethodmonitor the MVA response of every classifier
TTree*fMonitorTreetree to monitor values during the boosting
Double_tfOverlap_integral
Double_tfROC_trainingroc integral of last trained method (on training sample)
UInt_tfRandomSeedseed for random number generator used for bagging
vector<TH1*>fTestBgdMVAHist
vector<TH1*>fTestSigMVAHist
vector<TH1*>fTrainBgdMVAHist
vector<TH1*>fTrainSigMVAHist
TStringfTransformStringmin and max values for the classifier response

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

MethodBoost(const TString& jobName, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption = "", TDirectory* theTargetDir = NULL)
MethodBoost(TMVA::DataSetInfo& dsi, const TString& theWeightFile, TDirectory* theTargetDir = NULL)
~MethodBoost( void )
 destructor
Bool_t HasAnalysisType(TMVA::Types::EAnalysisType type, UInt_t numberClasses, UInt_t )
 Boost can handle classification with 2 classes and regression with one regression-target
void DeclareOptions()
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 weightfile at hand
Bool_t BookMethod(TMVA::Types::EMVA theMethod, TString methodTitle, TString theOption)
 just registering the string from which the boosted classifier will be created
void Init()
void InitHistos()
 initialisation routine
void CheckSetup()
void Train()
void CleanBoostOptions()
void CreateMVAHistorgrams()
void ResetBoostWeights()
 resetting back the boosted weights of the events to 1
void WriteMonitoringHistosToFile( void )
void TestClassification()
void WriteEvaluationHistosToFile(TMVA::Types::ETreeType treetype)
void ProcessOptions()
 process user options
void SingleTrain()
 initialization
void FindMVACut(TMVA::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 SingleBoost(TMVA::MethodBase* method)
Double_t AdaBoost(TMVA::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
void GetHelpMessage() const
 Get help message text

 typical length of text line:
         "|--------------------------------------------------------------|"
const TMVA::Ranking* CreateRanking()
Double_t GetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)
 return boosted MVA response
Double_t GetBoostROCIntegral(Bool_t , TMVA::Types::ETreeType , Bool_t CalcOverlapIntergral = kFALSE)
 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'
void CalcMVAValues()
 Calculate MVA values of current method fMethods.back() on
 training sample
void MonitorBoost(TMVA::Types::EBoostStage stage, UInt_t methodIdx = 0)
 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
void SetBoostedMethodName(TString methodName)
{ fBoostedMethodName = methodName; }
Int_t GetBoostNum()
{ return fBoostNum; }
void ClearAll()
 clean up
void PrintResults(const TString& , vector<Double_t>& , const Double_t ) const
 print fit results
MethodBase* CurrentMethod()
{return fCurrentMethod;}
UInt_t CurrentMethodIdx()
 training a single classifier
{return fCurrentMethodIdx;}
Double_t CalcMethodWeight()
 calculate weight of single method