[14365] | 1 | using System;
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| 2 | using System.Linq;
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| 3 | using HeuristicLab.Core;
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| 4 | using HeuristicLab.Problems.DataAnalysis;
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| 5 |
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| 6 |
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| 7 | namespace RegressionProblemInstances {
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| 8 | // This is a general descriptor for regression problem instances which produces data for a given target expression
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| 9 | public class RegressionProblemInstanceDescriptor : IRegressionProblemInstanceDescriptor {
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| 10 | private IRandom rand;
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| 11 | private int dim;
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| 12 | private Func<double[], double> func;
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| 13 | private int numRows;
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| 14 |
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| 15 | public string Name { get; }
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| 16 | public string Description { get; }
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| 17 |
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| 18 | public RegressionProblemInstanceDescriptor(string name, string desc, IRandom rand, int numRows, int dim, Func<double[], double> func) {
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| 19 | this.Name = name;
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| 20 | this.Description = desc;
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| 21 | this.rand = rand;
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| 22 | this.numRows = numRows;
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| 23 | this.dim = dim;
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| 24 | this.func = func;
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| 25 | }
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| 26 |
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| 27 |
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| 28 | public IRegressionProblemData GenerateData() {
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| 29 | var inputs = Enumerable.Range(1, dim).Select(idx => "x" + idx);
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| 30 | var target = "y";
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| 31 |
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| 32 | // generate data
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| 33 | var x = new double[dim]; // for evaluating the expression
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| 34 | var data = new double[numRows, dim + 1];
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| 35 | int i = 0;
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| 36 | while (i < numRows) {
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| 37 | for (int j = 0; j < dim; j++) {
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| 38 | // we use the supplied PRND to generate x independently and identically distributed
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| 39 | // the PRND could use any kind of probability distribution
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| 40 | x[j] = rand.NextDouble();
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| 41 | data[i, j] = x[j];
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| 42 | }
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| 43 | data[i, dim] = func(x); // y = f(x)
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| 44 | // only accept reasonable values
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| 45 | if (!double.IsInfinity(data[i, dim]) && !double.IsNaN(data[i, dim])) i++;
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| 46 | }
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| 47 |
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| 48 | var ds = new Dataset(inputs.Concat(new string[] { target }), data);
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| 49 | ds.Name = Name;
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| 50 | var probData = new RegressionProblemData(ds, inputs, target);
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| 51 | probData.Name = Name;
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| 52 | return probData;
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| 53 | }
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| 54 |
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| 55 | }
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| 56 | }
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