1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using HeuristicLab.Data;
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25 |
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26 | namespace HeuristicLab.Problems.DataAnalysis.Benchmarks {
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27 | public class KornFunctionFourteen : RegressionToyBenchmark {
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28 |
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29 | public KornFunctionFourteen() {
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30 | Name = "Korn 14 y = 22.0 + (4.2 * ((cos(X0) - tan(X1)) * (tanh(X2) / sin(X3))))";
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31 | Description = "Paper: Accuracy in Symbolic Regression" + Environment.NewLine
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32 | + "Authors: Michael F. Korns" + Environment.NewLine
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33 | + "Function: y = 22.0 + (4.2 * ((cos(X0) - tan(X1)) * (tanh(X2) / sin(X3))))" + Environment.NewLine
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34 | + "Real Numbers: 3.45, -.982, 100.389, and all other real constants" + Environment.NewLine
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35 | + "Row Features: x1, x2, x9, and all other features" + Environment.NewLine
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36 | + "Binary Operators: +, -, *, /" + Environment.NewLine
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37 | + "Unary Operators: sqrt, square, cube, cos, sin, tan, tanh, log, exp" + Environment.NewLine
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38 | + "\"Our testing regimen uses only statistical best practices out-of-sample testing techniques. "
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39 | + "We test each of the test cases on matrices of 10000 rows by 1 to 5 columns with no noise. "
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40 | + "For each test a training matrix is filled with random numbers between -50 and +50. The test case "
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41 | + "target expressions are limited to one basis function whose maximum depth is three grammar nodes.\"";
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42 | targetVariable = "Y";
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43 | inputVariables = new List<string>() { "X0", "X1", "X2", "X3", "X4" };
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44 | trainingPartition = new IntRange(0, 5000);
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45 | testPartition = new IntRange(5001, 10000);
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46 | }
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47 |
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48 | protected override List<double> GenerateTarget(List<List<double>> data) {
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49 | double x0, x1, x2, x3;
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50 | List<double> results = new List<double>();
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51 | for (int i = 0; i < data[0].Count; i++) {
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52 | x0 = data[0][i];
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53 | x1 = data[1][i];
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54 | x2 = data[2][i];
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55 | x3 = data[3][i];
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56 | results.Add(22.0 + (4.2 * ((Math.Cos(x0) - Math.Tan(x1)) * (Math.Tanh(x2) / Math.Sin(x3)))));
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57 | }
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58 | return results;
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59 | }
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60 |
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61 | protected override List<List<double>> GenerateInput() {
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62 | List<List<double>> dataList = new List<List<double>>();
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63 | DoubleRange range = new DoubleRange(-50, 50);
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64 | for (int i = 0; i < inputVariables.Count; i++) {
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65 | dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
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66 | }
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67 |
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68 | return dataList;
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69 | }
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70 | }
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71 | }
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