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Reference Guide
MethodBayesClassifier.h
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1// @(#)root/tmva $Id$
2// Author: Abhishek Narain
3
4/**********************************************************************************
5 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6 * Package: TMVA *
7 * Class : MethodBayesClassifier *
8 * Web : http://tmva.sourceforge.net *
9 * *
10 * Description: *
11 * Bayesian Classifier *
12 * *
13 * Authors (alphabetical): *
14 * Abhishek Narain, <narainabhi@gmail.com> - University of Houston *
15 * *
16 * Copyright (c) 2005-2006: *
17 * University of Houston, *
18 * CERN, Switzerland *
19 * U. of Victoria, Canada *
20 * MPI-K Heidelberg, Germany *
21 * LAPP, Annecy, France *
22 * *
23 * Redistribution and use in source and binary forms, with or without *
24 * modification, are permitted according to the terms listed in LICENSE *
25 * (http://tmva.sourceforge.net/LICENSE) *
26 **********************************************************************************/
27
28#ifndef ROOT_TMVA_MethodBayesClassifier
29#define ROOT_TMVA_MethodBayesClassifier
30
31//////////////////////////////////////////////////////////////////////////
32// //
33// MethodBayesClassifier //
34// //
35// Description... //
36// //
37//////////////////////////////////////////////////////////////////////////
38
39#include "TMVA/MethodBase.h"
40#include "TMVA/Types.h"
41
42namespace TMVA {
43
45
46 public:
47
48 MethodBayesClassifier( const TString& jobName,
49 const TString& methodTitle,
50 DataSetInfo& theData,
51 const TString& theOption = "");
52
54 const TString& theWeightFile);
55
56 virtual ~MethodBayesClassifier( void );
57
58 virtual Bool_t HasAnalysisType( Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets );
59
60 // training method
61 void Train( void );
62
64
65 // write weights to file
66 void AddWeightsXMLTo( void* parent ) const;
67
68 // read weights from file
69 void ReadWeightsFromStream( std::istream& istr );
70 void ReadWeightsFromXML ( void* /*wghtnode*/ ) {}
71
72 // calculate the MVA value
73 Double_t GetMvaValue( Double_t* err = 0, Double_t* errUpper = 0 );
74
75 void Init( void );
76
77 // ranking of input variables
78 const Ranking* CreateRanking() { return 0; }
79
80 protected:
81
82 // make ROOT-independent C++ class for classifier response (classifier-specific implementation)
83 void MakeClassSpecific( std::ostream&, const TString& ) const;
84
85 // get help message text
86 void GetHelpMessage() const;
87
88 private:
89
90 // the option handling methods
91 void DeclareOptions();
92 void ProcessOptions();
93
94 ClassDef(MethodBayesClassifier,0); // Friedman's BayesClassifier method
95 };
96
97} // namespace TMVA
98
99#endif // MethodBayesClassifier_H
unsigned int UInt_t
Definition: RtypesCore.h:46
bool Bool_t
Definition: RtypesCore.h:63
double Double_t
Definition: RtypesCore.h:59
#define ClassDef(name, id)
Definition: Rtypes.h:325
int type
Definition: TGX11.cxx:121
Class that contains all the data information.
Definition: DataSetInfo.h:62
Virtual base Class for all MVA method.
Definition: MethodBase.h:111
virtual void ReadWeightsFromStream(std::istream &)=0
Description of bayesian classifiers.
void GetHelpMessage() const
get help message text
void ProcessOptions()
the option string is decoded, for available options see "DeclareOptions"
virtual ~MethodBayesClassifier(void)
destructor
Double_t GetMvaValue(Double_t *err=0, Double_t *errUpper=0)
returns MVA value for given event
void MakeClassSpecific(std::ostream &, const TString &) const
write specific classifier response
void ReadWeightsFromStream(std::istream &istr)
read back the training results from a file (stream)
void AddWeightsXMLTo(void *parent) const
void DeclareOptions()
define the options (their key words) that can be set in the option string
MethodBayesClassifier(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
standard constructor
virtual Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
Variable can handle classification with 2 classes.
void Init(void)
default initialisation
Ranking for variables in method (implementation)
Definition: Ranking.h:48
EAnalysisType
Definition: Types.h:128
Basic string class.
Definition: TString.h:136
create variable transformations