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File indexing completed on 2025-01-30 10:23:03
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 : SeparationBase * 0008 * * 0009 * * 0010 * Description: An interface to different separation criteria used in various * 0011 * training algorithms, as there are: * 0012 * Gini-Index, Cross Entropy, Misclassification Error, e.t.c. * 0013 * * 0014 * There are two things: the Separation Index, and the Separation Gain * 0015 * Separation Index: * 0016 * Measure of the "purity" of a sample. If all elements (events) in the * 0017 * sample belong to the same class (e.g. signal or backgr), than the * 0018 * separation index is 0 (meaning 100% purity (or 0% purity as it is * 0019 * symmetric. The index becomes maximal, for perfectly mixed samples * 0020 * eg. purity=50% , N_signal = N_bkg * 0021 * * 0022 * Separation Gain: * 0023 * the measure of how the quality of separation of the sample increases * 0024 * by splitting the sample e.g. into a "left-node" and a "right-node" * 0025 * (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right) * 0026 * this is then the quality criterion which is optimized for when trying * 0027 * to increase the information in the system (making the best selection * 0028 * * 0029 * * 0030 * Authors (alphabetical): * 0031 * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland * 0032 * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany * 0033 * Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada * 0034 * * 0035 * Copyright (c) 2005: * 0036 * CERN, Switzerland * 0037 * U. of Victoria, Canada * 0038 * Heidelberg U., Germany * 0039 * * 0040 * Redistribution and use in source and binary forms, with or without * 0041 * modification, are permitted according to the terms listed in LICENSE * 0042 * (see tmva/doc/LICENSE) * 0043 **********************************************************************************/ 0044 0045 #ifndef ROOT_TMVA_SeparationBase 0046 #define ROOT_TMVA_SeparationBase 0047 0048 ////////////////////////////////////////////////////////////////////////// 0049 // // 0050 // SeparationBase // 0051 // // 0052 // An interface to calculate the "SeparationGain" for different // 0053 // separation criteria used in various training algorithms // 0054 // // 0055 // There are two things: the Separation Index, and the Separation Gain // 0056 // Separation Index: // 0057 // Measure of the "purity" of a sample. If all elements (events) in the // 0058 // sample belong to the same class (e.g. signal or background), than the// 0059 // separation index is 0 (meaning 100% purity (or 0% purity as it is // 0060 // symmetric. The index becomes maximal, for perfectly mixed samples // 0061 // eg. purity=50% , N_signal = N_bkg // 0062 // // 0063 // Separation Gain: // 0064 // the measure of how the quality of separation of the sample increases // 0065 // by splitting the sample e.g. into a "left-node" and a "right-node" // 0066 // (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right) // 0067 // this is then the quality criterion which is optimized for when trying// 0068 // to increase the information in the system (making the best selection // 0069 // // 0070 ////////////////////////////////////////////////////////////////////////// 0071 0072 #include "Rtypes.h" 0073 0074 #include "TString.h" 0075 0076 #include "TMath.h" 0077 0078 #include <limits> 0079 0080 namespace TMVA { 0081 0082 class SeparationBase { 0083 0084 public: 0085 0086 // default constructor 0087 SeparationBase(); 0088 0089 //copy constructor 0090 SeparationBase( const SeparationBase& s ); 0091 0092 // destructor 0093 virtual ~SeparationBase(){} 0094 0095 // Return the gain in separation of the original sample is split in two sub-samples 0096 // (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right) 0097 virtual Double_t GetSeparationGain( const Double_t nSelS, const Double_t nSelB, 0098 const Double_t nTotS, const Double_t nTotB ); 0099 0100 // Return the separation index (a measure for "purity" of the sample") 0101 virtual Double_t GetSeparationIndex( const Double_t s, const Double_t b ) = 0; 0102 0103 // Return the name of the concrete Index implementation 0104 const TString& GetName() { return fName; } 0105 0106 protected: 0107 0108 TString fName; // name of the concrete Separation Index implementation 0109 0110 Double_t fPrecisionCut; 0111 0112 ClassDef(SeparationBase,0); // Interface to different separation criteria used in training algorithms 0113 }; 0114 0115 0116 } // namespace TMVA 0117 0118 #endif
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