#region License Information /* HeuristicLab * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab 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 General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Linq; namespace HeuristicLab.Problems.Instances.DataAnalysis { public class NguyenFunctionFour : ArtificialRegressionDataDescriptor { public override string Name { get { return "Nguyen F4 = x^6 + x^5 + x^4 + x³ + x² + x"; } } public override string Description { get { return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine + "Function: F4 = x^6 + x^5 + x^4 + x³ + x² + x" + Environment.NewLine + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine + "Terminals: only variables (no random constants)"; } } protected override string TargetVariable { get { return "Y"; } } protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } protected override int TrainingPartitionStart { get { return 0; } } protected override int TrainingPartitionEnd { get { return 20; } } protected override int TestPartitionStart { get { return 250; } } protected override int TestPartitionEnd { get { return 350; } } protected override List> GenerateValues() { List> data = new List>(); data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList()); double x; List results = new List(); for (int i = 0; i < data[0].Count; i++) { x = data[0][i]; results.Add(Math.Pow(x, 6) + Math.Pow(x, 5) + Math.Pow(x, 4) + Math.Pow(x, 3) + Math.Pow(x, 2) + x); } data.Add(results); return data; } } }