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File indexing completed on 2025-01-30 10:22:52
0001 // @(#)root/tmva $Id$ 0002 // Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss 0003 0004 /********************************************************************************** 0005 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis * 0006 * Package: TMVA * 0007 * Class : GiniIndexWithLaplace * 0008 * * 0009 * * 0010 * Description: Implementation of the GiniIndex With Laplace correction * 0011 * as separation criterion * 0012 * * 0013 * Authors (alphabetical): * 0014 * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland * 0015 * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany * 0016 * Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada * 0017 * * 0018 * Copyright (c) 2005: * 0019 * CERN, Switzerland * 0020 * U. of Victoria, Canada * 0021 * Heidelberg U., Germany * 0022 * * 0023 * Redistribution and use in source and binary forms, with or without * 0024 * modification, are permitted according to the terms listed in LICENSE * 0025 * (http://ttmva.sourceforge.net/LICENSE) * 0026 **********************************************************************************/ 0027 0028 #ifndef ROOT_TMVA_GiniIndexWithLaplace 0029 #define ROOT_TMVA_GiniIndexWithLaplace 0030 0031 ////////////////////////////////////////////////////////////////////////// 0032 // // 0033 // GiniIndexWithLaplace // 0034 // // 0035 // Implementation of the GiniIndex With Laplace correction // 0036 // as separation criterion // 0037 // // 0038 // Large Gini Indices (maximum 0.5) mean , that the sample is well // 0039 // mixed (same amount of signal and bkg) // 0040 // bkg. Small Indices mean, well separated. // 0041 // general definition: // 0042 // Gini(Sample M) = 1 - (c(1)/N)^2 - (c(2)/N)^2 .... - (c(k)/N)^2 // 0043 // Where: M is a sample of whatever N elements (events) // 0044 // that belong to K different classes // 0045 // c(k) is the number of elements that belong to class k // 0046 // for just Signal and Background classes this boils down to: // 0047 // The Laplace's correction to the probability distribution would // 0048 // turn the c(1)/N into (c(1)+1)/(N+2) // 0049 // using this the simple Gini Index for two classes // 0050 // Gini(Sample) = 2s*b/(s+b)^2 // 0051 // turns into // 0052 // GiniLaplace(Sample) = 2(s*b+s+b+1)/(s+b+2)^2 // 0053 ////////////////////////////////////////////////////////////////////////// 0054 0055 #include "TMVA/SeparationBase.h" 0056 0057 namespace TMVA { 0058 0059 class GiniIndexWithLaplace : public SeparationBase { 0060 0061 public: 0062 0063 // construtor for the GiniIndexWithLaplace 0064 GiniIndexWithLaplace() { fName="GiniLaplace"; } 0065 0066 // copy constructor 0067 GiniIndexWithLaplace( const GiniIndexWithLaplace& g): SeparationBase(g) {} 0068 0069 //destructor 0070 virtual ~GiniIndexWithLaplace(){} 0071 0072 // Return the separation index (a measure for "purity" of the sample") 0073 virtual Double_t GetSeparationIndex( const Double_t s, const Double_t b ); 0074 0075 protected: 0076 0077 ClassDef(GiniIndexWithLaplace,0); // Implementation of the GiniIndexWithLaplace as separation criterion 0078 }; 0079 0080 } // namespace TMVA 0081 0082 #endif 0083
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