ROOT  6.06/09
Reference Guide
MCFitter.h
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1 // @(#)root/tmva $Id$
2 // Author: Andreas Hoecker, Peter Speckmayer, Joerg Stelzer, Helge Voss
3 
4 /**********************************************************************************
5  * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6  * Package: TMVA *
7  * Class : MCFitter *
8  * Web : http://tmva.sourceforge.net *
9  * *
10  * Description: *
11  * Fitter using Monte Carlo sampling of parameters *
12  * *
13  * Authors (alphabetical): *
14  * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
15  * Peter Speckmayer <speckmay@mail.cern.ch> - CERN, Switzerland *
16  * Joerg Stelzer <Joerg.Stelzer@cern.ch> - CERN, Switzerland *
17  * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
18  * *
19  * Copyright (c) 2005: *
20  * CERN, Switzerland *
21  * MPI-K Heidelberg, Germany *
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_MCFitter
29 #define ROOT_TMVA_MCFitter
30 
31 //////////////////////////////////////////////////////////////////////////
32 // //
33 // MCFitter //
34 // //
35 // Fitter using Monte Carlo sampling of parameters //
36 // //
37 //////////////////////////////////////////////////////////////////////////
38 
39 #ifndef ROOT_TMVA_FitterBase
40 #include "TMVA/FitterBase.h"
41 #endif
42 
43 namespace TMVA {
44 
45  class MCFitter : public FitterBase {
46 
47  public:
48 
49  MCFitter( IFitterTarget& target, const TString& name,
50  const std::vector<TMVA::Interval*>& ranges, const TString& theOption );
51 
52  virtual ~MCFitter() {}
53 
54  void SetParameters( Int_t cycles );
55 
56  Double_t Run( std::vector<Double_t>& pars );
57 
58  private:
59 
60  void DeclareOptions();
61 
62  Int_t fSamples; // number of MC samples
63  Double_t fSigma; // new samples are generated randomly with a gaussian probability with fSigma around the current best value
64  UInt_t fSeed; // Seed for the random generator (0 takes random seeds)
65 
66  ClassDef(MCFitter,0) // Fitter using Monte Carlo sampling of parameters
67  };
68 
69 } // namespace TMVA
70 
71 #endif
72 
73 
Double_t fSigma
Definition: MCFitter.h:63
Int_t fSamples
Definition: MCFitter.h:62
Basic string class.
Definition: TString.h:137
int Int_t
Definition: RtypesCore.h:41
#define ClassDef(name, id)
Definition: Rtypes.h:254
Double_t Run()
estimator function interface for fitting
Definition: FitterBase.cxx:73
void SetParameters(Int_t cycles)
set MC fitter configuration parameters
Definition: MCFitter.cxx:76
UInt_t fSeed
Definition: MCFitter.h:64
unsigned int UInt_t
Definition: RtypesCore.h:42
virtual ~MCFitter()
Definition: MCFitter.h:52
void DeclareOptions()
Declare MCFitter options.
Definition: MCFitter.cxx:65
double Double_t
Definition: RtypesCore.h:55
#define name(a, b)
Definition: linkTestLib0.cpp:5
Abstract ClassifierFactory template that handles arbitrary types.
MCFitter(IFitterTarget &target, const TString &name, const std::vector< TMVA::Interval * > &ranges, const TString &theOption)