// @(#)root/tmva $Id: MethodHMatrix.h 21630 2008-01-10 19:40:44Z brun $ // Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss /********************************************************************************** * Project: TMVA - a Root-integrated toolkit for multivariate data analysis * * Package: TMVA * * Class : MethodHMatrix * * Web : http://tmva.sourceforge.net * * * * Description: * * H-Matrix method, which is implemented as a simple comparison of * * chi-squared estimators for signal and background, taking into account * * the linear correlations between the input variables. * * Method is (also) used by D0 Collaboration (FNAL) for electron * * identification; for more information, see, eg, * * http://www-d0.fnal.gov/d0dist/dist/packages/tau_hmchisq/devel/doc/ * * * * Authors (alphabetical): * * Andreas Hoecker - CERN, Switzerland * * Xavier Prudent - LAPP, France * * Helge Voss - MPI-K Heidelberg, Germany * * Kai Voss - U. of Victoria, Canada * * * * Copyright (c) 2005: * * CERN, Switzerland * * U. of Victoria, Canada * * MPI-K Heidelberg, Germany * * LAPP, Annecy, France * * * * Redistribution and use in source and binary forms, with or without * * modification, are permitted according to the terms listed in LICENSE * * (http://tmva.sourceforge.net/LICENSE) * **********************************************************************************/ #ifndef ROOT_TMVA_MethodHMatrix #define ROOT_TMVA_MethodHMatrix ////////////////////////////////////////////////////////////////////////// // // // MethodHMatrix // // // // H-Matrix method, which is implemented as a simple comparison of // // chi-squared estimators for signal and background, taking into // // account the linear correlations between the input variables // // // ////////////////////////////////////////////////////////////////////////// #ifndef ROOT_TMVA_MethodBase #include "TMVA/MethodBase.h" #endif #ifndef ROOT_TMVA_TMatrixD #include "TMatrixD.h" #endif #ifndef ROOT_TMVA_TVectorD #include "TVectorD.h" #endif namespace TMVA { class MethodHMatrix : public MethodBase { public: MethodHMatrix( const TString& jobName, const TString& methodTitle, DataSet& theData, const TString& theOption = "", TDirectory* theTargetDir = 0 ); MethodHMatrix( DataSet& theData, const TString& theWeightFile, TDirectory* theTargetDir = NULL ); virtual ~MethodHMatrix( void ); // training method void Train( void ); using MethodBase::WriteWeightsToStream; using MethodBase::ReadWeightsFromStream; // write weights to file void WriteWeightsToStream( ostream& o ) const; // read weights from file void ReadWeightsFromStream( istream& istr ); // calculate the MVA value Double_t GetMvaValue(); // ranking of input variables const Ranking* CreateRanking() { return 0; } protected: // make ROOT-independent C++ class for classifier response (classifier-specific implementation) void MakeClassSpecific( std::ostream&, const TString& ) const; // get help message text void GetHelpMessage() const; private: // the option handling methods void DeclareOptions(); void ProcessOptions(); // returns chi2 estimator for given type (signal or background) Double_t GetChi2( Event* e, Types::ESBType ) const; Double_t GetChi2( Types::ESBType ) const; // compute correlation matrices void ComputeCovariance( Bool_t, TMatrixD* ); // arrays of input evt vs. variable TMatrixD* fInvHMatrixS; // inverse H-matrix (signal) TMatrixD* fInvHMatrixB; // inverse H-matrix (background) TVectorD* fVecMeanS; // vector of mean values (signal) TVectorD* fVecMeanB; // vector of mean values (background) // default initialisation method called by all constructors void InitHMatrix( void ); ClassDef(MethodHMatrix,0) // H-Matrix method, a simple comparison of chi-squared estimators for signal and background }; } // namespace TMVA #endif