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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