[17400] | 1 | using System;
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| 2 | using System.Collections;
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| 3 | using System.Collections.Generic;
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| 4 | using System.Linq;
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| 5 | using HeuristicLab.Common;
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| 6 | using HeuristicLab.Core;
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| 7 | using HeuristicLab.Problems.DataAnalysis;
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| 8 | using HeuristicLab.Random;
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| 9 |
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| 10 | namespace HeuristicLab.Problems.Instances.DataAnalysis {
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| 11 | public class AzzaliBenchmark3 : ArtificialRegressionDataDescriptor {
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| 12 | public override string Name { get { return "Azzali Benchmark2 B3 = "; } }
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| 13 | public override string Description { get { return "I. Azzali, L. Vanneschi, S. Silva, I. Bakurov, and M. Giacobini, “A Vectorial Approach to Genetic Programming,” EuroGP, pp. 213–227, 2019."; } }
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| 14 |
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| 15 | protected override string TargetVariable { get { return "B3"; } }
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| 16 | protected override string[] VariableNames { get { return new string[] { "X1", "X2", "X3", "X4" }; } }
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| 17 | protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4" }; } }
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| 18 | protected override int TrainingPartitionStart { get { return 0; } }
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| 19 | protected override int TrainingPartitionEnd { get { return 70; } }
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| 20 | protected override int TestPartitionStart { get { return 70; } }
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| 21 | protected override int TestPartitionEnd { get { return 100; } }
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| 22 |
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| 23 | public int Seed { get; private set; }
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| 24 |
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| 25 | public AzzaliBenchmark3()
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| 26 | : this((int)DateTime.Now.Ticks) { }
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| 27 | public AzzaliBenchmark3(int seed)
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| 28 | : base() {
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| 29 | Seed = seed;
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| 30 | }
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| 31 |
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| 32 |
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| 33 | protected override List<List<double>> GenerateValues() { return null; }
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| 34 | protected override List<IList> GenerateValuesExtended() {
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| 35 | var rand = new MersenneTwister((uint)Seed);
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| 36 |
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| 37 | var x1Column = new List<DoubleVector>(100);
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| 38 | var x2Column = new List<double>(100);
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| 39 | var x3Column = new List<double>(100);
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| 40 | var x4Column = new List<double>(100);
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| 41 | var x5Column = new List<double>(100);
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| 42 | var b3Column = new List<DoubleVector>(100);
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| 43 |
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| 44 | for (int i = 0; i < 100; i++) {
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| 45 | var x1 = rand.NextDoubleVector(10, 30, 20);
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| 46 | var x2 = rand.NextDouble(50, 60);
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| 47 | var x3 = rand.NextDouble(5, 10);
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| 48 | var x4 = rand.NextDouble(-2, +2);
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| 49 | var x5 = rand.NextDouble(0, 1);
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| 50 |
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| 51 | int p = 3, q = 3;
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| 52 | var cumulativeMin = new DoubleVector(
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| 53 | Enumerable.Range(0, x1.Count)
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| 54 | .Select(idx => Enumerable.Range(idx - p, q)) // build index ranges for each target entry
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| 55 | .Select(indices => indices.Select(idx => idx < 0 ? 0 : x1[idx])) // take the values from the vector (fill with 0 if outside)
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| 56 | .Select(values => values.Min())
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| 57 | );
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| 58 | var b3 = (cumulativeMin * (x2 / x3)) + x4;
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| 59 |
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| 60 | x1Column.Add(x1);
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| 61 | x2Column.Add(x2);
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| 62 | x3Column.Add(x3);
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| 63 | x4Column.Add(x4);
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| 64 | b3Column.Add(b3);
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| 65 | }
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| 66 |
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| 67 | return new List<IList> { x1Column, x2Column, x3Column, x4Column, x5Column, b3Column };
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| 68 | }
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| 69 | }
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| 70 | } |
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