Free cookie consent management tool by TermsFeed Policy Generator

source: branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Keijzer/KeijzerFunctionEight.cs @ 7025

Last change on this file since 7025 was 7025, checked in by sforsten, 13 years ago

#1669: benchmark problems of Nguyen, Korns and Keijzer from http://groups.csail.mit.edu/EVO-DesignOpt/GPBenchmarks/ have been added. The benchmark problems from http://www.vanillamodeling.com/ have been adapted to the ones from Vladislavleva.

Not all benchmarks are working correctly so far, but they will be tested soon.

File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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 HeuristicLab.Data;
25
26namespace HeuristicLab.Problems.DataAnalysis.Benchmarks {
27  public class KeijzerFunctionEight : RegressionBenchmark {
28
29    public KeijzerFunctionEight() {
30      Name = "Keijzer 8 f(x) = log(x)";
31      Description = "Paper: Improving Symbolic Regression with Interval Arithmetic and Linear Scaling" + Environment.NewLine
32        + "Authors: Maarten Keijzer" + Environment.NewLine
33        + "Function: f(x) = log(x)" + Environment.NewLine
34        + "range(train): x = [0:1:100]" + Environment.NewLine
35        + "range(test): x = [0:0.1:100]" + Environment.NewLine
36        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
37      targetVariable = "F";
38      inputVariables = new List<string>() { "X", "Y", "Z" };
39      trainingPartition = new IntRange(0, 101);
40      testPartition = new IntRange(102, 1103);
41    }
42
43    protected override List<double> CalculateFunction(List<List<double>> data) {
44      double x;
45      List<double> results = new List<double>();
46      for (int i = 0; i < data[0].Count; i++) {
47        x = data[0][i];
48        results.Add(Math.Log(x));
49      }
50      return results;
51    }
52
53    protected override List<List<double>> GenerateInput(List<List<double>> dataList) {
54      dataList.Add(RegressionBenchmark.GenerateSteps(new DoubleRange(0, 100), 1));
55      dataList[0].AddRange(RegressionBenchmark.GenerateSteps(new DoubleRange(0, 100), 0.1));
56
57      return dataList;
58    }
59  }
60}
Note: See TracBrowser for help on using the repository browser.