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source: trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTwelve.cs @ 8238

Last change on this file since 8238 was 8238, checked in by gkronber, 11 years ago

#1784 adapted Keijzer instances

File size: 3.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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 KeijzerFunctionTwelve : ArtificialRegressionDataDescriptor {
28
29    public override string Name { get { return "Keijzer 12 f(x, y) = x^4 - x³ + y² / 2 - y"; } }
30    public override string Description {
31      get {
32        return "Paper: Improving Symbolic Regression with Interval Arithmetic and Linear Scaling" + Environment.NewLine
33        + "Authors: Maarten Keijzer" + Environment.NewLine
34        + "Function: f(x, y) = x^4 - x³ + y² / 2 - y" + Environment.NewLine
35        + "range(train): 20 Training cases x,y = rnd(-3, 3)" + Environment.NewLine
36        + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
37        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
38        + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
39        + ", but 5000 cases are created";
40      }
41    }
42    protected override string TargetVariable { get { return "F"; } }
43    protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } }
44    protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
45    protected override int TrainingPartitionStart { get { return 0; } }
46    protected override int TrainingPartitionEnd { get { return 20; } }
47    protected override int TestPartitionStart { get { return 2500; } }
48    protected override int TestPartitionEnd { get { return 2600; } }
49
50    protected override List<List<double>> GenerateValues() {
51      List<List<double>> data = new List<List<double>>();
52      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
53        data.Add(ValueGenerator.GenerateUniformDistributedValues(5000, -3, 3).ToList());
54      }
55
56      double x, y;
57      List<double> results = new List<double>();
58      for (int i = 0; i < data[0].Count; i++) {
59        x = data[0][i];
60        y = data[1][i];
61        results.Add(Math.Pow(x, 4) - Math.Pow(x, 3) + Math.Pow(y, 2) / 2 - y);
62      }
63      data.Add(results);
64
65      return data;
66    }
67  }
68}
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