library: libTMVA
#include "MethodTMlpANN.h"

TMVA::MethodTMlpANN

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

class TMVA::MethodTMlpANN : public TMVA::MethodBase, public TMVA::MethodANNBase

Inheritance Chart:

TObject

TMVA::MethodBase

TMVA::MethodANNBase

TMVA::MethodTMlpANN

    private:

      void CreateMLPOptions()
      void InitTMlpANN()

    public:

                           MethodTMlpANN(TString jobName, vector<TString>* theVariables, TTree* theTree = 0, TString theOption = 3000:N-1:N-2, TDirectory* theTargetDir = 0)
                           MethodTMlpANN(vector<TString>* theVariables, TString theWeightFile, TDirectory* theTargetDir = NULL)
                           MethodTMlpANN(const TMVA::MethodTMlpANN&)
                   virtual ~MethodTMlpANN()
            static TClass* Class()
          virtual Double_t GetMvaValue(TMVA::Event*)
           virtual TClass* IsA() const
      TMVA::MethodTMlpANN& operator=(const TMVA::MethodTMlpANN&)
              virtual void PrepareEvaluationTree(TTree* testTree)
              virtual void ReadWeightsFromFile()
                      void SetHiddenLayer(TString hiddenlayer = )
                      void SetTestTree(TTree* testTree)
              virtual void ShowMembers(TMemberInspector& insp, char* parent)
              virtual void Streamer(TBuffer& b)
                      void StreamerNVirtual(TBuffer& b)
              virtual void Train()
              virtual void WriteHistosToFile()
              virtual void WriteWeightsToFile()

Data Members

    private:

      TString fHiddenLayer  string containig the hidden layer structure
        Int_t fNcycles      number of training cylcles
       TTree* fTestTree     TestTree

Class Description

_______________________________________________________________________

This is the TMVA TMultiLayerPerceptron interface class. It provides the training and testing the ROOT internal MLP class in the TMVA framework. Available learning methods:

TMultiLayerPerceptron::kStochastic
TMultiLayerPerceptron::kBatch
TMultiLayerPerceptron::kSteepestDescent
TMultiLayerPerceptron::kRibierePolak
TMultiLayerPerceptron::kFletcherReeves
TMultiLayerPerceptron::kBFGS

See the MethodTMlpANN( TString jobName, std::vector<TString>* theVariables, TTree* theTree, TString theOption, TDirectory* theTargetDir)

 standard constructor
 option string is interpreted in base class: MethodANNBase

MethodTMlpANN( vector<TString> *theVariables, TString theWeightFile, TDirectory* theTargetDir )

 constructor to calculate the TMlpANN-MVA from previously generatad
 weigths (weight file)

void InitTMlpANN( void )

 default initialisations

~MethodTMlpANN( void )

 destructor

void CreateMLPOptions( void )

 translates options from option string into TMlpANN language

void Train( void )

 performs TMlpANN training
 available learning methods:

       TMultiLayerPerceptron::kStochastic
       TMultiLayerPerceptron::kBatch
       TMultiLayerPerceptron::kSteepestDescent
       TMultiLayerPerceptron::kRibierePolak
       TMultiLayerPerceptron::kFletcherReeves
       TMultiLayerPerceptron::kBFGS

void WriteWeightsToFile( void )

 write weights to file

void ReadWeightsFromFile( void )

 read weights from file

void PrepareEvaluationTree( TTree* testTree )

 evaluate method

void SetTestTree( TTree* testTree )

 set the test tree

void WriteHistosToFile( void )

 write special monitoring histograms to file - not implemented for TMlpANN

MethodTMlpANN( TString jobName, vector<TString>* theVariables, TTree* theTree = 0, TString theOption = "3000:N-1:N-2", TDirectory* theTargetDir = 0 )

void SetHiddenLayer(TString hiddenlayer = "" )

Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss
Last update: root/tmva $Id: MethodTMlpANN.cxx,v 1.3 2006/05/23 19:35:06 brun Exp $
Copyright (c) 2005: *

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