1 | using System.Collections.Generic;
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2 | using HEAL.Attic;
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3 | using HeuristicLab.Common;
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4 | using HeuristicLab.Core;
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5 | using HeuristicLab.Data;
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6 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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7 |
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8 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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9 | [Item("Pearson R² Constraint Evaluator",
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10 | "Calculates the square of the pearson correlation coefficient (also known as coefficient of determination) of a symbolic regression solution.")]
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11 | [StorableType("D61462E4-2032-4790-B63D-5E6512987F64")]
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12 | public class SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator : SymbolicRegressionSingleObjectiveEvaluator {
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13 | [StorableConstructor]
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14 | protected SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(StorableConstructorFlag _) :
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15 | base(_) { }
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16 |
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17 | protected SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(
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18 | SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator original, Cloner cloner)
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19 | : base(original, cloner) { }
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20 |
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21 | public override IDeepCloneable Clone(Cloner cloner) {
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22 | return new SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(this, cloner);
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23 | }
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24 |
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25 | public SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator() { }
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26 |
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27 | public override bool Maximization => true;
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28 |
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29 | public override IOperation InstrumentedApply() {
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30 | var solution = SymbolicExpressionTreeParameter.ActualValue;
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31 | var rows = GenerateRowsToEvaluate();
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32 |
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33 | var quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution,
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34 | EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper,
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35 | ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value);
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36 | QualityParameter.ActualValue = new DoubleValue(quality);
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37 | return base.InstrumentedApply();
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38 | }
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39 |
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40 | public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
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41 | ISymbolicExpressionTree solution, double lowerEstimationLimit,
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42 | double upperEstimationLimit, IRegressionProblemData problemData,
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43 | IEnumerable<int> rows, bool applyLinearScaling) {
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44 | var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
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45 | var targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
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46 | var errorState = OnlineCalculatorError.None;
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47 |
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48 | var constraints = problemData.IntervalConstraints.EnabledConstraints;
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49 | var variableRanges = problemData.VariableRanges.GetDictionary();
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50 | var tree = solution;
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51 |
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52 | if (!SymbolicRegressionConstraintAnalyzer.ConstraintsSatisfied(constraints, variableRanges, tree)) return 0;
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53 |
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54 | var r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, solution,
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55 | lowerEstimationLimit,
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56 | upperEstimationLimit, problemData,
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57 | rows, applyLinearScaling);
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58 |
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59 | return r2;
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60 | }
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61 |
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62 |
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63 | public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree,
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64 | IRegressionProblemData problemData, IEnumerable<int> rows) {
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65 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
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66 | EstimationLimitsParameter.ExecutionContext = context;
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67 | ApplyLinearScalingParameter.ExecutionContext = context;
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68 |
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69 | var r2 = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree,
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70 | EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper,
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71 | problemData, rows,
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72 | ApplyLinearScalingParameter.ActualValue.Value);
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73 |
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74 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
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75 | EstimationLimitsParameter.ExecutionContext = null;
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76 | ApplyLinearScalingParameter.ExecutionContext = null;
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77 |
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78 | return r2;
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79 | }
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80 | }
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81 | } |
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