119 lines
3.5 KiB
C++
119 lines
3.5 KiB
C++
/*
|
|
* Open BEAGLE
|
|
* Copyright (C) 2001-2007 by Christian Gagne and Marc Parizeau
|
|
*
|
|
* This library is free software; you can redistribute it and/or
|
|
* modify it under the terms of the GNU Lesser General Public
|
|
* License as published by the Free Software Foundation; either
|
|
* version 2.1 of the License, or (at your option) any later version.
|
|
*
|
|
* This library is distributed in the hope that it will be useful,
|
|
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
* Lesser General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU Lesser General Public
|
|
* License along with this library; if not, write to the Free Software
|
|
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
|
|
*
|
|
* Contact:
|
|
* Laboratoire de Vision et Systemes Numeriques
|
|
* Departement de genie electrique et de genie informatique
|
|
* Universite Laval, Quebec, Canada, G1K 7P4
|
|
* http://vision.gel.ulaval.ca
|
|
*
|
|
*/
|
|
|
|
/*!
|
|
* \file SymbRegEvalOp.hpp
|
|
* \brief Definition of the type SymbRegEvalOp.
|
|
* \author Christian Gagne
|
|
* \author Marc Parizeau
|
|
* $Revision: 1.5.2.1 $
|
|
* $Date: 2007/05/09 01:51:24 $
|
|
*/
|
|
|
|
/*!
|
|
* \defgroup SymbReg Symbolic Regression Example
|
|
* \brief Symbolic regression (symbreg): A simple GP example with Open BEAGLE.
|
|
*
|
|
* \par Objective
|
|
* Find a function of one independent variable and one dependent variable, in
|
|
* symbolic form, that fits a given sample of 20 \f$(x_i,y_i)\f$ data points,
|
|
* where the target function is the quadratic polynomial \f$x^4 + x^3 + x^2 + x\f$.
|
|
*
|
|
* \par Terminal set
|
|
* - X (the independent variable)
|
|
* - PI
|
|
* - Ephemeral constants randomly generated in [-1,1]
|
|
*
|
|
* \par Function set
|
|
* - +
|
|
* - -
|
|
* - *
|
|
* - / (protected division)
|
|
* - SIN
|
|
* - COS
|
|
* - EXP
|
|
* - LOG (protected logarithm)
|
|
*
|
|
* \par Fitness cases
|
|
* The given sample of 20 data points \f$(x_i,y_i)\f$, randomly chosen within
|
|
* interval [-1,1].
|
|
*
|
|
* \par Fitness
|
|
* \f$\frac{1.}{1.+RMSE}\f$ where RMSE is the Root Mean Square Error on the
|
|
* fitness cases.
|
|
*
|
|
* \par Stopping criteria
|
|
* When the evolution reaches the maximum number of generations.
|
|
*
|
|
* \par Reference
|
|
* John R. Koza, "Genetic Programming: On the Programming of Computers by Means
|
|
* of Natural Selection", MIT Press, 1992, pages 162-169.
|
|
*
|
|
*/
|
|
|
|
#ifndef SymbRegEvalOp_hpp
|
|
#define SymbRegEvalOp_hpp
|
|
|
|
#include "beagle/GP.hpp"
|
|
|
|
#include <string>
|
|
#include <vector>
|
|
|
|
|
|
|
|
/*!
|
|
* \class SymbRegEvalOp SymbRegEvalOp.hpp "SymbRegEvalOp.hpp"
|
|
* \brief The individual evaluation class operator for the problem of symbolic regression.
|
|
* \ingroup SymbReg
|
|
*/
|
|
class SymbRegEvalOp : public Beagle::GP::EvaluationOp {
|
|
|
|
public:
|
|
|
|
//! SymbRegEvalOp allocator type.
|
|
typedef Beagle::AllocatorT<SymbRegEvalOp,Beagle::GP::EvaluationOp::Alloc>
|
|
Alloc;
|
|
//!< SymbRegEvalOp handle type.
|
|
typedef Beagle::PointerT<SymbRegEvalOp,Beagle::GP::EvaluationOp::Handle>
|
|
Handle;
|
|
//!< SymbRegEvalOp bag type.
|
|
typedef Beagle::ContainerT<SymbRegEvalOp,Beagle::GP::EvaluationOp::Bag>
|
|
Bag;
|
|
|
|
explicit SymbRegEvalOp(std::string inName="SymbRegEvalOp");
|
|
|
|
virtual Beagle::Fitness::Handle evaluate(Beagle::GP::Individual& inIndividual,
|
|
Beagle::GP::Context& ioContext);
|
|
virtual void postInit(Beagle::System& ioSystem);
|
|
|
|
protected:
|
|
std::vector<Beagle::Double> mX;
|
|
std::vector<Beagle::Double> mY;
|
|
|
|
};
|
|
|
|
#endif // SymbRegEvalOp_hpp
|