#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 NguyenFunctionSeven : ArtificialRegressionDataDescriptor {
public override string Name { get { return "Nguyen F7 = log(x + 1) + log(x² + 1)"; } }
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: F7 = ln(x + 1) + ln(x² + 1)" + Environment.NewLine
+ "Fitcases: 20 random points in [0, 2]" + 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, 0, 2).ToList());
double x;
List results = new List();
for (int i = 0; i < data[0].Count; i++) {
x = data[0][i];
results.Add(Math.Log(x + 1) + Math.Log(Math.Pow(x, 2) + 1));
}
data.Add(results);
return data;
}
}
}