/usr/include/root/TMVA/MethodBayesClassifier.h is in libroot-tmva-dev 5.34.30-0ubuntu8.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | // @(#)root/tmva $Id$
// Author: Abhishek Narain
/**********************************************************************************
* Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
* Package: TMVA *
* Class : MethodBayesClassifier *
* Web : http://tmva.sourceforge.net *
* *
* Description: *
* Bayesian Classifier *
* *
* Authors (alphabetical): *
* Abhishek Narain, <narainabhi@gmail.com> - University of Houston *
* *
* Copyright (c) 2005-2006: *
* University of Houston, *
* 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_MethodBayesClassifier
#define ROOT_TMVA_MethodBayesClassifier
//////////////////////////////////////////////////////////////////////////
// //
// MethodBayesClassifier //
// //
// Description... //
// //
//////////////////////////////////////////////////////////////////////////
#ifndef ROOT_TMVA_MethodBase
#include "TMVA/MethodBase.h"
#endif
#ifndef ROOT_TMVA_Types
#include "TMVA/Types.h"
#endif
namespace TMVA {
class MethodBayesClassifier : public MethodBase {
public:
MethodBayesClassifier( const TString& jobName,
const TString& methodTitle,
DataSetInfo& theData,
const TString& theOption = "",
TDirectory* theTargetDir = 0 );
MethodBayesClassifier( DataSetInfo& theData,
const TString& theWeightFile,
TDirectory* theTargetDir = NULL );
virtual ~MethodBayesClassifier( void );
virtual Bool_t HasAnalysisType( Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets );
// training method
void Train( void );
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 = 0, Double_t* errUpper = 0 );
void Init( void );
// 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();
ClassDef(MethodBayesClassifier,0) // Friedman's BayesClassifier method
};
} // namespace TMVA
#endif // MethodBayesClassifier_H
|