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class TMVA::SdivSqrtSplusB: public TMVA::SeparationBase

Function Members (Methods)

public:
virtual~SdivSqrtSplusB()
static TClass*Class()
const TString&TMVA::SeparationBase::GetName()
virtual Double_tGetSeparationGain(const Double_t& nSelS, const Double_t& nSelB, const Double_t& nTotS, const Double_t& nTotB)
virtual Double_tGetSeparationIndex(const Double_t& s, const Double_t& b)
virtual TClass*IsA() const
TMVA::SdivSqrtSplusB&operator=(const TMVA::SdivSqrtSplusB&)
TMVA::SdivSqrtSplusBSdivSqrtSplusB()
TMVA::SdivSqrtSplusBSdivSqrtSplusB(const TMVA::SdivSqrtSplusB& g)
virtual voidShowMembers(TMemberInspector&)
virtual voidStreamer(TBuffer&)
voidStreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)

Data Members

protected:
TStringTMVA::SeparationBase::fNamename of the concrete Separation Index impementation
Double_tTMVA::SeparationBase::fPrecisionCut

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

Double_t GetSeparationIndex(const Double_t& s, const Double_t& b)
 Index = S/sqrt(S+B)  (statistical significance)
Double_t GetSeparationGain(const Double_t& nSelS, const Double_t& nSelB, const Double_t& nTotS, const Double_t& nTotB)
 Separation Gain:
 the measure of how the quality of separation of the sample increases
 by splitting the sample e.g. into a "left-node" and a "right-node"
 (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right)
 this is then the quality crition which is optimized for when trying
 to increase the information in the system (making the best selection
SdivSqrtSplusB()
constructor for the "statistical significance" index
{ fName = "StatSig"; }
SdivSqrtSplusB(const TMVA::SdivSqrtSplusB& g)
 copy constructor
{}
virtual ~SdivSqrtSplusB()
destructor
{}