// @(#)root/tmva $Id: MethodANNBase.h,v 1.2 2006/05/23 13:03:15 brun Exp $ // Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss /********************************************************************************** * Project: TMVA - a Root-integrated toolkit for multivariate data analysis * * Package: TMVA * * Class : MethodANNBase * * * * Description: * * Base class for all MVA methods based on artificial neural networks (ANN) * * contains common functionality * * * * Authors (alphabetical): * * Andreas Hoecker - CERN, Switzerland * * Xavier Prudent - LAPP, France * * Helge Voss - MPI-KP Heidelberg, Germany * * Kai Voss - U. of Victoria, Canada * * * * Copyright (c) 2005: * * CERN, Switzerland, * * U. of Victoria, Canada, * * MPI-KP Heidelberg, Germany, * * LAPP, Annecy, France * * * * Redistribution and use in source and binary forms, with or without * * modification, are permitted according to the terms listed in LICENSE * * (http://mva.sourceforge.net/license.txt) * * * **********************************************************************************/ #ifndef ROOT_TMVA_MethodANNBase #define ROOT_TMVA_MethodANNBase ////////////////////////////////////////////////////////////////////////// // // // MethodANNBase // // // // Base class for all MVA methods using artificial neural networks // // // ////////////////////////////////////////////////////////////////////////// #include "TString.h" #include namespace TMVA { class MethodANNBase { public: MethodANNBase( void ); virtual ~MethodANNBase() {} protected: // option string parser // first input in vector is number of cycles; additional inputs give // number of nodes for each layer (as many layers as inputs in vector) std::vector* ParseOptionString( TString, Int_t, std::vector* ); ClassDef(MethodANNBase,0) //Base class for all MVA methods using artificial neural networks }; } // namespace TMVA #endif