1 | PROBLEM SymbRegKoza
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2 | CODE <<
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3 | double[,] x;
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4 | double[] y;
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5 | string[] variableNames;
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6 | Dictionary<string,int> nameToCol;
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7 |
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8 | double GetValue(double[,] data, string varName, int row) {
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9 | if(nameToCol == null) {
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10 | /* init mapping */
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11 | nameToCol = new Dictionary<string, int>();
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12 | for(int i=0; i<variableNames.Length; i++) {
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13 | nameToCol[variableNames[i]] = i;
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14 | }
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15 | }
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16 | return x[row, nameToCol[varName]];
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17 | }
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18 |
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19 | double RSquared(IEnumerable<double> xs, IEnumerable<double> ys) {
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20 | HeuristicLab.Problems.DataAnalysis.OnlineCalculatorError error;
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21 | var r2 = HeuristicLab.Problems.DataAnalysis.OnlinePearsonsRSquaredCalculator.Calculate(xs, ys, out error);
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22 | if(error == HeuristicLab.Problems.DataAnalysis.OnlineCalculatorError.None) return r2;
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23 | else return 0.0;
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24 | }
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25 | >>
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26 |
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27 | INIT <<
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28 | // generate 500 case of poly-10 benchmark function
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29 | int n = 500;
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30 | variableNames = new string[] {"x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9", "x10" };
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31 | var rand = new System.Random();
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32 | x = new double[n, 10];
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33 | y = new double[n];
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34 | for(int row = 0; row < 500; row++) {
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35 | for(int col = 0; col < 10; col++) {
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36 | x[row, col] = rand.NextDouble() * 2.0 - 1.0;
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37 | }
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38 | y[row] = x[row, 0] * x[row, 1] +
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39 | x[row, 2] * x[row, 3] +
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40 | x[row, 4] * x[row, 5] +
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41 | x[row, 0] * x[row, 6] + x[row, 8] +
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42 | x[row, 2] * x[row, 5] + x[row, 9];
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43 | }
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44 | >>
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45 |
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46 | NONTERMINALS
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47 | Model<<int row, out double val>>.
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48 | RPB<<int row, out double val>>.
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49 | Addition<<int row, out double val>>.
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50 | Subtraction<<int row, out double val>>.
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51 | Multiplication<<int row, out double val>>.
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52 | Division<<int row, out double val>>.
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53 |
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54 | TERMINALS
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55 | ERC<<out double val>>
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56 | CONSTRAINTS
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57 | val IN RANGE <<-100>> .. <<100>>
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58 | .
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59 |
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60 | Var<<out string varName>>
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61 | CONSTRAINTS
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62 | varName IN SET <<variableNames>>
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63 | .
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64 |
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65 | RULES
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66 | Model<<int row, out double val>> =
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67 | RPB<<row, out val>> .
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68 |
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69 | RPB<<int row, out double val>> = LOCAL << string varName; >>
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70 | Addition<<row, out val>>
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71 | | Subtraction<<row, out val>>
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72 | | Division<<row, out val>>
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73 | | Multiplication<<row, out val>>
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74 | | Var<<out varName>> SEM << val = GetValue(x, varName, row); >>
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75 | | ERC<<out val>>
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76 | .
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77 |
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78 | Addition<<int row, out double val>> = LOCAL << double x1, x2; >>
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79 | RPB<<row, out x1>> RPB<<row, out x2>> SEM<< val = x1 + x2; >>
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80 | .
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81 | Subtraction<<int row, out double val>> = LOCAL << double x1, x2; >>
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82 | RPB<<row, out x1>> RPB<<row, out x2>> SEM<< val = x1 - x2; >>
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83 | .
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84 | Division<<int row, out double val>> = LOCAL << double x1, x2; >>
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85 | RPB<<row, out x1>> RPB<<row, out x2>> SEM<< val = x1 / x2; >>
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86 | .
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87 | Multiplication<<int row, out double val>> = LOCAL << double x1, x2; >>
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88 | RPB<<row, out x1>> RPB<<row, out x2>> SEM<< val = x1 * x2; >>
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89 | .
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90 |
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91 | MAXIMIZE /* could also use the keyword MINIMIZE here */
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92 | <<
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93 | var rows = System.Linq.Enumerable.Range(0, x.GetLength(0));
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94 | var predicted = rows.Select(r => {
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95 | double result;
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96 | Model(r, out result); /* we can call the root symbol directly */
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97 | return result;
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98 | });
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99 | return RSquared(predicted, y);
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100 | >>
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101 | END SymbRegKoza.
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