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SdivSqrtSplusB.h
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1 // @(#)root/tmva $Id$
2 // Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss
3 
4 /**********************************************************************************
5  * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6  * Package: TMVA *
7  * Class : SdivSqrtSplusB *
8  * Web : http://tmva.sourceforge.net *
9  * *
10  * Description: Implementation of the SdivSqrtSplusB as separation criterion *
11  * S/sqrt(S + B) *
12  * *
13  * Authors (alphabetical): *
14  * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
15  * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
16  * Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada *
17  * *
18  * Copyright (c) 2005: *
19  * CERN, Switzerland *
20  * U. of Victoria, Canada *
21  * Heidelberg U., Germany *
22  * *
23  * Redistribution and use in source and binary forms, with or without *
24  * modification, are permitted according to the terms listed in LICENSE *
25  * (http://tmva.sourceforge.net/LICENSE) *
26  **********************************************************************************/
27 
28 #ifndef ROOT_TMVA_SdivSqrtSplusB
29 #define ROOT_TMVA_SdivSqrtSplusB
30 
31 //////////////////////////////////////////////////////////////////////////
32 // //
33 // SdivSqrtSplusB //
34 // //
35 // Implementation of the SdivSqrtSplusB as separation criterion //
36 // Index = S/sqrt(S+B) (statistical significance) //
37 // //
38 //////////////////////////////////////////////////////////////////////////
39 
40 #include "TMVA/SeparationBase.h"
41 
42 namespace TMVA {
43 
44  class SdivSqrtSplusB : public SeparationBase {
45 
46  public:
47 
48  //constructor for the "statistical significance" index
49  SdivSqrtSplusB(): SeparationBase() { fName = "StatSig"; }
50 
51  // copy constructor
53 
54  //destructor
55  virtual ~SdivSqrtSplusB() {}
56 
57  // Return the gain in separation of the original sample is split in two sub-samples
58  // (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right)
59  virtual Double_t GetSeparationGain( const Double_t nSelS, const Double_t nSelB,
60  const Double_t nTotS, const Double_t nTotB );
61  // return the Index (S/sqrt(S+B))
62  virtual Double_t GetSeparationIndex( const Double_t s, const Double_t b );
63 
64  protected:
65 
66  ClassDef(SdivSqrtSplusB,0); // Implementation of the SdivSqrtSplusB as separation criterion
67  };
68 
69 } // namespace TMVA
70 
71 #endif
72 
#define g(i)
Definition: RSha256.hxx:105
#define ClassDef(name, id)
Definition: Rtypes.h:322
static constexpr double s
Implementation of the SdivSqrtSplusB as separation criterion.
virtual Double_t GetSeparationIndex(const Double_t s, const Double_t b)
Index = S/sqrt(S+B) (statistical significance)
An interface to calculate the "SeparationGain" for different separation criteria used in various trai...
SdivSqrtSplusB(const SdivSqrtSplusB &g)
virtual 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 th...
double Double_t
Definition: RtypesCore.h:57
create variable transformations
you should not use this method at all Int_t Int_t Double_t Double_t Double_t Int_t Double_t Double_t Double_t Double_t b
Definition: TRolke.cxx:630