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File indexing completed on 2025-12-27 11:37:37
0001 // Author: Krzysztof Danielowski, Kamil Kraszewski, Maciej Kruk, Jan Therhaag 0002 0003 /********************************************************************************** 0004 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis * 0005 * Package: TMVA * 0006 * Class : MethodLD * 0007 * * 0008 * * 0009 * Description: * 0010 * Linear Discriminant (Simple Linear Regression) * 0011 * * 0012 * Authors (alphabetical): * 0013 * Krzysztof Danielowski <danielow@cern.ch> - IFJ PAN & AGH, Poland * 0014 * Kamil Kraszewski <kalq@cern.ch> - IFJ PAN & UJ, Poland * 0015 * Maciej Kruk <mkruk@cern.ch> - IFJ PAN & AGH, Poland * 0016 * Peter Speckmayer <peter.speckmayer@cern.ch> - CERN, Switzerland * 0017 * Jan Therhaag <therhaag@physik.uni-bonn.de> - Uni Bonn, Germany * 0018 * * 0019 * Copyright (c) 2008-2011: * 0020 * CERN, Switzerland * 0021 * PAN, Poland * 0022 * U. of Bonn, Germany * 0023 * * 0024 * Redistribution and use in source and binary forms, with or without * 0025 * modification, are permitted according to the terms listed in LICENSE * 0026 * (see tmva/doc/LICENSE) * 0027 * * 0028 **********************************************************************************/ 0029 0030 #ifndef ROOT_TMVA_MethodLD 0031 #define ROOT_TMVA_MethodLD 0032 0033 ////////////////////////////////////////////////////////////////////////// 0034 // // 0035 // MethodLD // 0036 // // 0037 // Linear Discriminant // 0038 // Can compute multidimensional output for regression // 0039 // (although it computes every dimension separately) // 0040 // // 0041 ////////////////////////////////////////////////////////////////////////// 0042 0043 #include <vector> 0044 0045 #include "TMVA/MethodBase.h" 0046 #include "TMatrixDfwd.h" 0047 0048 namespace TMVA { 0049 0050 class MethodLD : public MethodBase { 0051 0052 public: 0053 0054 // constructor 0055 MethodLD( const TString& jobName, 0056 const TString& methodTitle, 0057 DataSetInfo& dsi, 0058 const TString& theOption = "LD"); 0059 0060 // constructor 0061 MethodLD( DataSetInfo& dsi, 0062 const TString& theWeightFile); 0063 0064 // destructor 0065 virtual ~MethodLD( void ); 0066 0067 Bool_t HasAnalysisType( Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets ) override; 0068 0069 // training method 0070 void Train( void ) override; 0071 0072 // calculate the MVA value 0073 Double_t GetMvaValue( Double_t* err = nullptr, Double_t* errUpper = nullptr ) override; 0074 0075 // calculate the Regression value 0076 const std::vector<Float_t>& GetRegressionValues() override; 0077 0078 using MethodBase::ReadWeightsFromStream; 0079 0080 void AddWeightsXMLTo ( void* parent ) const override; 0081 0082 void ReadWeightsFromStream( std::istream & i ) override; 0083 void ReadWeightsFromXML ( void* wghtnode ) override; 0084 0085 const Ranking* CreateRanking() override; 0086 void DeclareOptions() override; 0087 void ProcessOptions() override; 0088 0089 protected: 0090 0091 void MakeClassSpecific( std::ostream&, const TString& ) const override; 0092 void GetHelpMessage() const override; 0093 0094 private: 0095 0096 Int_t fNRegOut; ///< size of the output 0097 0098 TMatrixD *fSumMatx; ///< Sum of coordinates product matrix 0099 TMatrixD *fSumValMatx; ///< Sum of values multiplied by coordinates 0100 TMatrixD *fCoeffMatx; ///< Matrix of coefficients 0101 std::vector< std::vector<Double_t>* > *fLDCoeff; ///< LD coefficients 0102 0103 // default initialisation called by all constructors 0104 void Init( void ) override; 0105 0106 // Initialization and allocation of matrices 0107 void InitMatrices( void ); 0108 0109 // Compute fSumMatx 0110 void GetSum( void ); 0111 0112 // Compute fSumValMatx 0113 void GetSumVal( void ); 0114 0115 // get LD coefficients 0116 void GetLDCoeff( void ); 0117 0118 // nice output 0119 void PrintCoefficients( void ); 0120 0121 ClassDefOverride(MethodLD,0); //Linear discriminant analysis 0122 }; 0123 } // namespace TMVA 0124 0125 #endif // MethodLD_H
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