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GiniIndexWithLaplace.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 : GiniIndexWithLaplace *
8 * Web : http://tmva.sourceforge.net *
9 * *
10 * Description: Implementation of the GiniIndex With Laplace correction *
11 * as separation criterion *
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://ttmva.sourceforge.net/LICENSE) *
26 **********************************************************************************/
27
28#ifndef ROOT_TMVA_GiniIndexWithLaplace
29#define ROOT_TMVA_GiniIndexWithLaplace
30
31//////////////////////////////////////////////////////////////////////////
32// //
33// GiniIndexWithLaplace //
34// //
35// Implementation of the GiniIndex With Laplace correction //
36// as separation criterion //
37// //
38// Large Gini Indices (maximum 0.5) mean , that the sample is well //
39// mixed (same amount of signal and bkg) //
40// bkg. Small Indices mean, well separated. //
41// general definition: //
42// Gini(Sample M) = 1 - (c(1)/N)^2 - (c(2)/N)^2 .... - (c(k)/N)^2 //
43// Where: M is a sample of whatever N elements (events) //
44// that belong to K different classes //
45// c(k) is the number of elements that belong to class k //
46// for just Signal and Background classes this boils down to: //
47// The Laplace's correction to the probability distribution would //
48// turn the c(1)/N into (c(1)+1)/(N+2) //
49// using this the simple Gini Index for two classes //
50// Gini(Sample) = 2s*b/(s+b)^2 //
51// turns into //
52// GiniLaplace(Sample) = 2(s*b+s+b+1)/(s+b+2)^2 //
53//////////////////////////////////////////////////////////////////////////
54
55#include "TMVA/SeparationBase.h"
56
57namespace TMVA {
58
60
61 public:
62
63 // construtor for the GiniIndexWithLaplace
64 GiniIndexWithLaplace() { fName="GiniLaplace"; }
65
66 // copy constructor
68
69 //destructor
71
72 // Return the separation index (a measure for "purity" of the sample")
73 virtual Double_t GetSeparationIndex( const Double_t s, const Double_t b );
74
75 protected:
76
77 ClassDef(GiniIndexWithLaplace,0); // Implementation of the GiniIndexWithLaplace as separation criterion
78 };
79
80} // namespace TMVA
81
82#endif
83
double Double_t
Definition: RtypesCore.h:59
#define ClassDef(name, id)
Definition: Rtypes.h:335
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t b
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t g
Implementation of the GiniIndex With Laplace correction as separation criterion.
GiniIndexWithLaplace(const GiniIndexWithLaplace &g)
virtual Double_t GetSeparationIndex(const Double_t s, const Double_t b)
An interface to calculate the "SeparationGain" for different separation criteria used in various trai...
static constexpr double s
create variable transformations