library: libTMVA
#include "TMVA_MethodCFMlpANN.h"

TMVA_MethodCFMlpANN


class description - source file - inheritance tree (.pdf)

class TMVA_MethodCFMlpANN : public TMVA_MethodBase, public TMVA_MethodANNBase

Inheritance Chart:
TObject
<-
TMVA_MethodBase
TMVA_MethodANNBase
<-
TMVA_MethodCFMlpANN
    private:
Double_t EvalANN(vector<Double_t>*, Bool_t& isOK) void InitCFMlpANN() void NN_ava(Double_t*) Double_t NN_fonc(Int_t, Double_t) const public:
TMVA_MethodCFMlpANN(TString jobName, vector<TString>* theVariables, TTree* theTree = 0, TString theOption = 3000:N-1:N-2, TDirectory* theTargetDir = 0) TMVA_MethodCFMlpANN(vector<TString>* theVariables, TString theWeightFile, TDirectory* theTargetDir = NULL) TMVA_MethodCFMlpANN(const TMVA_MethodCFMlpANN&) virtual ~TMVA_MethodCFMlpANN() static TClass* Class() Int_t GetClass(Int_t ivar) const Double_t GetData(Int_t isel, Int_t ivar) const virtual Double_t GetMvaValue(TMVA_Event* e) virtual TClass* IsA() const TMVA_MethodCFMlpANN& operator=(const TMVA_MethodCFMlpANN&) virtual void ReadWeightsFromFile() virtual void ShowMembers(TMemberInspector& insp, char* parent) virtual void Streamer(TBuffer& b) void StreamerNVirtual(TBuffer& b) static TMVA_MethodCFMlpANN* This() virtual void Train() virtual void WriteHistosToFile() virtual void WriteWeightsToFile()

Data Members

    private:
static TMVA_MethodCFMlpANN* fgThis TMatrixT<float>* fData the (data,var) string vector<Int_t>* fClass the event class (1=signal, 2=background) Int_t fNevt Int_t fNsig Int_t fNbgd Int_t fNlayers Int_t fNcycles Int_t* fNodes Double_t* fXmaxNN Double_t* fXminNN Int_t fLayermNN Int_t* fNeuronNN Double_t*** fWNN Double_t** fWwNN Double_t** fYNN Double_t* fTempNN

Class Description

 Interface for Clermond-Ferrand artificial neural network

_______________________________________________________________________

TMVA_MethodCFMlpANN( TString jobName, vector<TString>* theVariables, TTree* theTree, TString theOption, TDirectory* theTargetDir ) : TMVA_MethodBase( jobName, theVariables, theTree, theOption, theTargetDir )

TMVA_MethodCFMlpANN( vector<TString> *theVariables, TString theWeightFile, TDirectory* theTargetDir ) : TMVA_MethodBase( theVariables, theWeightFile, theTargetDir )

void InitCFMlpANN( void )

~TMVA_MethodCFMlpANN( void )
 let's clean up

void Train( void )
--------------------------------------------------------------

Double_t GetMvaValue( TMVA_Event *e )

Double_t EvalANN( vector<Double_t>* inVar, Bool_t& isOK )

void NN_ava( Double_t* xeev )

Double_t NN_fonc( Int_t i, Double_t u ) const

void WriteWeightsToFile( void )
 write coefficients to file
 not used; weights are saved in TMVA_MethodCFMlpANN_f2c

void ReadWeightsFromFile( void )
 read coefficients from file

void WriteHistosToFile( void )



Inline Functions


                    Double_t GetData(Int_t isel, Int_t ivar) const
                       Int_t GetClass(Int_t ivar) const
        TMVA_MethodCFMlpANN* This()
                     TClass* Class()
                     TClass* IsA() const
                        void ShowMembers(TMemberInspector& insp, char* parent)
                        void Streamer(TBuffer& b)
                        void StreamerNVirtual(TBuffer& b)
         TMVA_MethodCFMlpANN TMVA_MethodCFMlpANN(const TMVA_MethodCFMlpANN&)
        TMVA_MethodCFMlpANN& operator=(const TMVA_MethodCFMlpANN&)


Author: Andreas Hoecker, Helge Voss, Kai Voss
Last update: root/tmva $Id: TMVA_MethodCFMlpANN.cxx,v 1.5 2006/05/09 08:37:06 brun Exp $
Copyright (c) 2005: *


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