[5500] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[15583] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5500] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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[16589] | 22 | using System;
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[5500] | 23 | using System.Collections.Generic;
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[16851] | 24 | using System.Linq;
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[16713] | 25 | using HEAL.Attic;
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[5500] | 26 | using HeuristicLab.Common;
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| 27 | using HeuristicLab.Core;
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| 28 | using HeuristicLab.Data;
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| 29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 30 |
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[5501] | 31 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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[16589] | 32 | [Item("Pearson R² Constraint Evaluator", "Calculates the square of the pearson correlation coefficient (also known as coefficient of determination) of a symbolic regression solution.")]
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[16628] | 33 | [StorableType("D61462E4-2032-4790-B63D-5E6512987F64")]
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[16589] | 34 | public class SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator : SymbolicRegressionSingleObjectiveEvaluator {
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[5500] | 35 | [StorableConstructor]
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[16628] | 36 | protected SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(StorableConstructorFlag _) : base(_) { }
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[16589] | 37 | protected SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator original, Cloner cloner)
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[5500] | 38 | : base(original, cloner) {
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| 39 | }
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| 40 | public override IDeepCloneable Clone(Cloner cloner) {
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[16589] | 41 | return new SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator(this, cloner);
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[5500] | 42 | }
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| 43 |
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[16589] | 44 | public SymbolicRegressionSingleObjectiveConstraintPearsonRSquaredEvaluator() : base() { }
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[5505] | 45 |
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[5514] | 46 | public override bool Maximization { get { return true; } }
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| 47 |
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[10291] | 48 | public override IOperation InstrumentedApply() {
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[5851] | 49 | var solution = SymbolicExpressionTreeParameter.ActualValue;
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[5500] | 50 | IEnumerable<int> rows = GenerateRowsToEvaluate();
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[5851] | 51 |
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[12977] | 52 | double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value);
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[5851] | 53 | QualityParameter.ActualValue = new DoubleValue(quality);
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[10291] | 54 | return base.InstrumentedApply();
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[5500] | 55 | }
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| 56 |
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[8664] | 57 | public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling) {
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[5500] | 58 | IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
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[8664] | 59 | IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
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[16596] | 60 | OnlineCalculatorError errorState = OnlineCalculatorError.None;
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[8664] | 61 |
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[16851] | 62 | var constraints = problemData.IntervalConstraints.Constraints.Where(x => x.Enabled);
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| 63 | var variableRanges = problemData.VariableRanges.VariableIntervals;
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| 64 | var tree = solution;
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[16589] | 65 |
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[12641] | 66 | double r;
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[8664] | 67 | if (applyLinearScaling) {
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[12641] | 68 | var rCalculator = new OnlinePearsonsRCalculator();
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| 69 | CalculateWithScaling(targetValues, estimatedValues, lowerEstimationLimit, upperEstimationLimit, rCalculator, problemData.Dataset.Rows);
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[16596] | 70 | var model = new SymbolicRegressionModel(problemData.TargetVariable, solution, interpreter, lowerEstimationLimit, upperEstimationLimit);
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| 71 | model.Scale(problemData);
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[16851] | 72 | tree = model.SymbolicExpressionTree;
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[12641] | 73 | errorState = rCalculator.ErrorState;
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[16851] | 74 | r = rCalculator.R;
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[8664] | 75 | } else {
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| 76 | IEnumerable<double> boundedEstimatedValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
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[16851] | 77 | r = OnlinePearsonsRCalculator.Calculate(targetValues, boundedEstimatedValues, out errorState);
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[8664] | 78 | }
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[16851] | 79 |
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| 80 | if (!SymbolicRegressionConstraintAnalyzer.ConstraintsSatisfied(constraints, variableRanges, tree)) {
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| 81 | return 0;
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| 82 | }
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| 83 |
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[8664] | 84 | if (errorState != OnlineCalculatorError.None) return double.NaN;
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[16713] | 85 | return r * r;
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[5500] | 86 | }
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[5613] | 87 |
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[16596] | 88 |
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[16592] | 89 | public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree,
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| 90 | IRegressionProblemData problemData, IEnumerable<int> rows) {
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[5722] | 91 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
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[5770] | 92 | EstimationLimitsParameter.ExecutionContext = context;
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[8664] | 93 | ApplyLinearScalingParameter.ExecutionContext = context;
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[5722] | 94 |
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[16592] | 95 | double r2 = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree,
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| 96 | EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows,
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| 97 | ApplyLinearScalingParameter.ActualValue.Value);
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[5722] | 98 |
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| 99 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
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[5770] | 100 | EstimationLimitsParameter.ExecutionContext = null;
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[8664] | 101 | ApplyLinearScalingParameter.ExecutionContext = null;
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[5722] | 102 |
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| 103 | return r2;
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[5613] | 104 | }
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[5500] | 105 | }
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| 106 | }
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