MethodHMatrix.h

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// @(#)root/tmva $Id$
// Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss
 
/**********************************************************************************
 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis       *
 * Package: TMVA                                                                  *
 * Class  : MethodHMatrix                                                         *
 *                                             *
 *                                                                                *
 * 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 <Andreas.Hocker@cern.ch> - CERN, Switzerland              *
 *      Helge Voss      <Helge.Voss@cern.ch>     - MPI-K Heidelberg, Germany      *
 *      Kai Voss        <Kai.Voss@cern.ch>       - U. of Victoria, Canada         *
 *                                                                                *
 * Copyright (c) 2005:                                                            *
 *      CERN, Switzerland                                                         *
 *      U. of Victoria, Canada                                                    *
 *      MPI-K Heidelberg, Germany                                                 *
 *                                                                                *
 * Redistribution and use in source and binary forms, with or without             *
 * modification, are permitted according to the terms listed in LICENSE           *
 * (see tmva/doc/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          //
//                                                                      //
//////////////////////////////////////////////////////////////////////////
 
#include "TMVA/MethodBase.h"
#include "TMatrixDfwd.h"
#include "TVectorD.h"
 
namespace TMVA {
 
   class MethodHMatrix : public MethodBase {
 
   public:
 
      MethodHMatrix( const TString& jobName,
                     const TString& methodTitle,
                     DataSetInfo& theData,
                     const TString& theOption = "");
 
      MethodHMatrix( DataSetInfo& theData,
                     const TString& theWeightFile);
 
      virtual ~MethodHMatrix();
 
      virtual Bool_t HasAnalysisType( Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets );
 
      // training method
      void Train();
 
      using MethodBase::ReadWeightsFromStream;
 
      // write weights to file
      void AddWeightsXMLTo( void* parent ) const;
 
      // read weights from file
      void ReadWeightsFromStream( std::istream& istr );
      void ReadWeightsFromXML( void* wghtnode );
      // calculate the MVA value
      Double_t GetMvaValue( Double_t* err = nullptr, Double_t* errUpper = nullptr );
 
      // ranking of input variables
      const Ranking* CreateRanking() { return nullptr; }
 
   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( Types::ESBType );
 
      // 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 Init();
 
      ClassDef(MethodHMatrix,0); // H-Matrix method, a simple comparison of chi-squared estimators for signal and background
   };
 
} // namespace TMVA
 
#endif