00001 // @(#)root/tmva $Id: ConvergenceTest.h 29122 2009-06-22 06:51:30Z brun $ 00002 // Author: Andreas Hoecker, Joerg Stelzer, Helge Voss 00003 00004 /********************************************************************************** 00005 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis * 00006 * Package: TMVA * 00007 * Class : ConvergenceTest * 00008 * Web : http://tmva.sourceforge.net * 00009 * * 00010 * Description: * 00011 * Contains all the data information * 00012 * * 00013 * Authors (alphabetical): * 00014 * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland * 00015 * Peter Speckmayer <Peter.Speckmayer@cern.ch> - CERN, Switzerland * 00016 * Joerg Stelzer <Joerg.Stelzer@cern.ch> - CERN, Switzerland * 00017 * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany * 00018 * * 00019 * Copyright (c) 2006: * 00020 * CERN, Switzerland * 00021 * U. of Victoria, Canada * 00022 * MPI-K Heidelberg, Germany * 00023 * * 00024 * Redistribution and use in source and binary forms, with or without * 00025 * modification, are permitted according to the terms listed in LICENSE * 00026 * (http://tmva.sourceforge.net/LICENSE) * 00027 **********************************************************************************/ 00028 00029 #ifndef ROOT_TMVA_ConvergenceTest 00030 #define ROOT_TMVA_ConvergenceTest 00031 00032 ////////////////////////////////////////////////////////////////////////// 00033 // // 00034 // ConvergenceTest // 00035 // // 00036 // check for convergence // 00037 // // 00038 ////////////////////////////////////////////////////////////////////////// 00039 00040 #include <deque> 00041 00042 #ifndef ROOT_Rtypes 00043 #include "Rtypes.h" 00044 #endif 00045 00046 namespace TMVA { 00047 00048 class ConvergenceTest { 00049 00050 public: 00051 00052 ConvergenceTest(); 00053 ~ConvergenceTest(); 00054 00055 // setters 00056 void SetConvergenceParameters( Int_t steps, Double_t improvement ) 00057 { fSteps = steps; fImprovement = improvement; } 00058 void SetCurrentValue( Float_t value ) { fCurrentValue = value; } 00059 Float_t GetCurrentValue() { return fCurrentValue; } 00060 void ResetConvergenceCounter() { fCounter = -1; fMaxCounter = 0; } 00061 00062 // getters 00063 Bool_t HasConverged( Bool_t withinConvergenceBand = kFALSE ); 00064 Float_t Progress(); // from 0 (just started) to 1 (finished) 00065 Float_t SpeedControl( UInt_t ofSteps ); 00066 00067 00068 protected: 00069 00070 Float_t fCurrentValue; //! current value 00071 00072 Float_t fImprovement; //! minimum improvement which counts as improvement 00073 Int_t fSteps; //! number of steps without improvement required for convergence 00074 00075 private: 00076 00077 Int_t fCounter; //! counts the number of steps without improvement 00078 Float_t fConvValue; //! the best "fitness" value 00079 Int_t fMaxCounter; //! maximum value for the counter so far 00080 00081 // speed-control (gives back the learning speed = improvement-rate in the last N steps) 00082 // successList keeps track of the improvements to be able 00083 Float_t fBestResult; // 00084 Float_t fLastResult; // 00085 std::deque<Short_t> fSuccessList; // to calculate the improvement-speed 00086 00087 }; 00088 } 00089 00090 #endif
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