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ConvergenceTest.h
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1// @(#)root/tmva $Id$
2// Author: Andreas Hoecker, Joerg Stelzer, Helge Voss
3
4/**********************************************************************************
5 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6 * Package: TMVA *
7 * Class : ConvergenceTest *
8 * Web : http://tmva.sourceforge.net *
9 * *
10 * Description: *
11 * Contains all the data information *
12 * *
13 * Authors (alphabetical): *
14 * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
15 * Peter Speckmayer <Peter.Speckmayer@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) 2006: *
20 * CERN, Switzerland *
21 * U. of Victoria, Canada *
22 * MPI-K Heidelberg, Germany *
23 * *
24 * Redistribution and use in source and binary forms, with or without *
25 * modification, are permitted according to the terms listed in LICENSE *
26 * (http://tmva.sourceforge.net/LICENSE) *
27 **********************************************************************************/
28
29#ifndef ROOT_TMVA_ConvergenceTest
30#define ROOT_TMVA_ConvergenceTest
31
32//////////////////////////////////////////////////////////////////////////
33// //
34// ConvergenceTest //
35// //
36// check for convergence //
37// //
38//////////////////////////////////////////////////////////////////////////
39
40#include <deque>
41
42#include "RtypesCore.h"
43
44namespace TMVA {
45
47
48 public:
49
52
53 // setters
54 void SetConvergenceParameters( Int_t steps, Double_t improvement )
55 { fSteps = steps; fImprovement = improvement; }
56 void SetCurrentValue( Float_t value ) { fCurrentValue = value; }
59
60 // getters
61 Bool_t HasConverged( Bool_t withinConvergenceBand = kFALSE );
62 Float_t Progress(); // from 0 (just started) to 1 (finished)
63 Float_t SpeedControl( UInt_t ofSteps );
64
65
66 protected:
67
68 Float_t fCurrentValue; //! current value
69
70 Float_t fImprovement; //! minimum improvement which counts as improvement
71 Int_t fSteps; //! number of steps without improvement required for convergence
72
73 private:
74
75 Int_t fCounter; //! counts the number of steps without improvement
76 Float_t fConvValue; //! the best "fitness" value
77 Int_t fMaxCounter; //! maximum value for the counter so far
78
79 // speed-control (gives back the learning speed = improvement-rate in the last N steps)
80 // successList keeps track of the improvements to be able
83 std::deque<Short_t> fSuccessList; // to calculate the improvement-speed
84
85 };
86}
87
88#endif
int Int_t
Definition: CPyCppyy.h:43
unsigned int UInt_t
Definition: CPyCppyy.h:44
const Bool_t kFALSE
Definition: RtypesCore.h:101
bool Bool_t
Definition: RtypesCore.h:63
double Double_t
Definition: RtypesCore.h:59
float Float_t
Definition: RtypesCore.h:57
Check for convergence.
Float_t fBestResult
maximum value for the counter so far
void SetConvergenceParameters(Int_t steps, Double_t improvement)
Int_t fMaxCounter
the best "fitness" value
Bool_t HasConverged(Bool_t withinConvergenceBand=kFALSE)
gives back true if the last "steps" steps have lead to an improvement of the "fitness" of the "indivi...
void SetCurrentValue(Float_t value)
Float_t Progress()
returns a float from 0 (just started) to 1 (finished)
std::deque< Short_t > fSuccessList
Int_t fCounter
number of steps without improvement required for convergence
Float_t SpeedControl(UInt_t ofSteps)
this function provides the ability to change the learning rate according to the success of the last g...
Float_t fImprovement
current value
ConvergenceTest()
constructor
Float_t fConvValue
counts the number of steps without improvement
Int_t fSteps
minimum improvement which counts as improvement
create variable transformations