[7025] | 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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[7044] | 27 | public class KornsFunctionEleven : RegressionToyBenchmark {
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[7025] | 28 |
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| 29 | public KornsFunctionEleven() {
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| 30 | Name = "Korn 11 y = 6.87 + (11 * cos(7.23 * X0 * X0 * X0))";
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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 = 6.87 + (11 * cos(7.23 * X0 * X0 * X0))" + 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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[7095] | 43 | inputVariables = new List<string>() { "X0", "X1", "X2", "X3", "X4" };
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[7025] | 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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[7044] | 48 | protected override List<double> GenerateTarget(List<List<double>> data) {
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[7025] | 49 | double x0;
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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 | results.Add(6.87 + (11 * Math.Cos(7.23 * x0 * x0 * x0)));
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| 54 | }
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| 55 | return results;
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| 56 | }
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| 57 |
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[7044] | 58 | protected override List<List<double>> GenerateInput() {
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| 59 | List<List<double>> dataList = new List<List<double>>();
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[7025] | 60 | DoubleRange range = new DoubleRange(-50, 50);
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| 61 | for (int i = 0; i < inputVariables.Count; i++) {
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| 62 | dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
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| 63 | }
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| 64 |
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| 65 | return dataList;
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| 66 | }
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| 67 | }
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| 68 | }
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