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source: stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionTen.cs @ 13689

Last change on this file since 13689 was 12009, checked in by ascheibe, 10 years ago

#2212 updated copyright year

File size: 2.9 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25
26namespace HeuristicLab.Problems.Instances.DataAnalysis {
27  public class NguyenFunctionTen : ArtificialRegressionDataDescriptor {
28
29    public override string Name { get { return "Nguyen F10 = 2sin(x)cos(y)"; } }
30    public override string Description {
31      get {
32        return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
33        + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
34        + "Function: F10 = 2sin(x)cos(y)" + Environment.NewLine
35        + "Fitcases: 20 random points in [0, 1]x[0, 1]" + Environment.NewLine
36        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
37        + "Terminals: only variables (no random constants)";
38      }
39    }
40    protected override string TargetVariable { get { return "Z"; } }
41    protected override string[] VariableNames { get { return new string[] { "X", "Y", "Z" }; } }
42    protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
43    protected override int TrainingPartitionStart { get { return 0; } }
44    protected override int TrainingPartitionEnd { get { return 20; } }
45    protected override int TestPartitionStart { get { return 20; } }
46    protected override int TestPartitionEnd { get { return 1020; } }
47
48    protected override List<List<double>> GenerateValues() {
49      List<List<double>> data = new List<List<double>>();
50      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
51      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
52
53      double x, y;
54      List<double> results = new List<double>();
55      for (int i = 0; i < data[0].Count; i++) {
56        x = data[0][i];
57        y = data[1][i];
58        results.Add(2 * Math.Sin(x) * Math.Cos(y));
59      }
60      data.Add(results);
61
62      return data;
63    }
64  }
65}
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