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

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

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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
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 KeijzerFunctionSeven : ArtificialRegressionDataDescriptor {
28
29    public override string Name { get { return "Keijzer 7 f(x) = ln(x)"; } }
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) = ln(x)" + Environment.NewLine
35          + "range(train): x = [1:1:100]" + Environment.NewLine
36          + "range(test): x = [1:0.1:100]" + Environment.NewLine
37          + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
38          + "Note: The problem starts with 1 to avoid log(0), which is minus infinity!";
39      }
40    }
41    protected override string TargetVariable { get { return "F"; } }
42    protected override string[] InputVariables { get { return new string[] { "X", "F" }; } }
43    protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } }
44    protected override int TrainingPartitionStart { get { return 0; } }
45    protected override int TrainingPartitionEnd { get { return 100; } }
46    protected override int TestPartitionStart { get { return 100; } }
47    protected override int TestPartitionEnd { get { return 1091; } }
48
49    protected override List<List<double>> GenerateValues() {
50      List<List<double>> data = new List<List<double>>();
53
54      double x;
55      List<double> results = new List<double>();
56      for (int i = 0; i < data[0].Count; i++) {
57        x = data[0][i];