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32 #ifndef ROOT_TMVA_MethodBoost
33 #define ROOT_TMVA_MethodBoost
55 namespace Experimental {
69 const TString& theOption =
"" );
void CreateMVAHistorgrams()
std::vector< TH1 * > fBTrainBgdMVAHist
TString fBoostedMethodOptions
void SetBoostedMethodName(TString methodName)
Ranking for variables in method (implementation)
UInt_t CurrentMethodIdx()
void InitHistos()
initialisation routine
void CheckSetup()
check may be overridden by derived class (sometimes, eg, fitters are used which can only be implement...
A TTree represents a columnar dataset.
virtual void TestClassification()
initialization
std::vector< TH1 * > fTestBgdMVAHist
void FindMVACut(MethodBase *method)
find the CUT on the individual MVA that defines an event as correct or misclassified (to be used in t...
Bool_t fHistoricBoolOption
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 GetHelpMessage() const
Get help message text.
Virtual base class for combining several TMVA method.
Bool_t fDetailedMonitoring
std::vector< TH1 * > fTrainBgdMVAHist
Class that contains all the data information.
std::vector< TH1 * > fBTrainSigMVAHist
void ProcessOptions()
process user options
Double_t CalcMethodWeight()
Double_t SingleBoost(MethodBase *method)
void ResetBoostWeights()
resetting back the boosted weights of the events to 1
Class for boosting a TMVA method.
std::vector< TH1 * > fTrainSigMVAHist
Double_t fBaggedSampleFraction
MethodBase * fCurrentMethod
virtual Double_t GetMvaValue(Double_t *errLower=0, Double_t *errUpper=0)=0
void SingleTrain()
initialization
This is the main MVA steering class.
void PrintResults(const TString &, std::vector< Double_t > &, const Double_t) const
void WriteMonitoringHistosToFile(void) const
write special monitoring histograms to file dummy implementation here --------------—
Virtual base Class for all MVA method.
std::vector< Float_t > * fMVAvalues
Double_t fOverlap_integral
const Ranking * CreateRanking()
void MonitorBoost(Types::EBoostStage stage, UInt_t methodIdx=0)
fill various monitoring histograms from information of the individual classifiers that have been boos...
std::vector< TH1 * > fTestSigMVAHist
TString fBoostedMethodName
TString fBoostedMethodTitle
Class that contains all the data information.
Double_t AdaBoost(MethodBase *method, Bool_t useYesNoLeaf)
the standard (discrete or real) AdaBoost algorithm
Bool_t fMonitorBoostedMethod
DataSetManager * fDataSetManager
#define ClassDef(name, id)
TH1 is the base class of all histogram classes in ROOT.
virtual ~MethodBoost(void)
destructor
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.
The Reader class serves to use the MVAs in a specific analysis context.
MethodBase * CurrentMethod()
Class to perform two class classification.
void DeclareCompatibilityOptions()
options that are used ONLY for the READER to ensure backward compatibility they are hence without any...
Bool_t BookMethod(Types::EMVA theMethod, TString methodTitle, TString theOption)
just registering the string from which the boosted classifier will be created
Double_t Bagging()
Bagging or Bootstrap boosting, gives new random poisson weight for every event.
create variable transformations
virtual void WriteEvaluationHistosToFile(Types::ETreeType treetype)
writes all MVA evaluation histograms to file