[8935] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[14185] | 3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8935] | 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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[10469] | 22 | using System;
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[8935] | 23 | using System.Collections.Generic;
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[8409] | 24 | using HeuristicLab.Common;
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[10469] | 25 | using HeuristicLab.Core;
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[8409] | 26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[10469] | 27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[8409] | 28 |
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| 29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
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[10469] | 30 | [StorableClass]
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| 31 | [Item("SymbolicClassificationSolutionImpactValuesCalculator", "Calculate symbolic expression tree node impact values for classification problems.")]
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[8946] | 32 | public class SymbolicClassificationSolutionImpactValuesCalculator : SymbolicDataAnalysisSolutionImpactValuesCalculator {
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[10469] | 33 | public SymbolicClassificationSolutionImpactValuesCalculator() { }
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| 34 | protected SymbolicClassificationSolutionImpactValuesCalculator(SymbolicClassificationSolutionImpactValuesCalculator original, Cloner cloner)
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| 35 | : base(original, cloner) { }
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| 36 | public override IDeepCloneable Clone(Cloner cloner) {
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| 37 | return new SymbolicClassificationSolutionImpactValuesCalculator(this, cloner);
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| 38 | }
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| 39 | [StorableConstructor]
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| 40 | protected SymbolicClassificationSolutionImpactValuesCalculator(bool deserializing) : base(deserializing) { }
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| 41 |
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[14826] | 42 | public override void CalculateImpactAndReplacementValues(ISymbolicDataAnalysisModel model,
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| 43 | ISymbolicExpressionTreeNode node,
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| 44 | IDataAnalysisProblemData problemData, IEnumerable<int> rows, out double impactValue, out double replacementValue,
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| 45 | out double newQualityForImpactsCalculation,
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[12720] | 46 | double qualityForImpactsCalculation = Double.NaN) {
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[8946] | 47 | var classificationModel = (ISymbolicClassificationModel)model;
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| 48 | var classificationProblemData = (IClassificationProblemData)problemData;
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| 49 |
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[12720] | 50 | if (double.IsNaN(qualityForImpactsCalculation))
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| 51 | qualityForImpactsCalculation = CalculateQualityForImpacts(classificationModel, classificationProblemData, rows);
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[8946] | 52 |
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[10273] | 53 |
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[8946] | 54 | var cloner = new Cloner();
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| 55 | var tempModel = cloner.Clone(classificationModel);
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[10273] | 56 | var tempModelNode = (ISymbolicExpressionTreeNode)cloner.GetClone(node);
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[8409] | 57 |
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[10273] | 58 | var tempModelParentNode = tempModelNode.Parent;
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| 59 | int i = tempModelParentNode.IndexOfSubtree(tempModelNode);
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[14826] | 60 | double bestReplacementValue = 0.0;
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| 61 | double bestImpactValue = double.PositiveInfinity;
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| 62 | newQualityForImpactsCalculation = qualityForImpactsCalculation; // initialize
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| 63 | // try the potentially reasonable replacement values and use the best one
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| 64 | foreach (var repValue in CalculateReplacementValues(node, classificationModel.SymbolicExpressionTree, classificationModel.Interpreter, classificationProblemData.Dataset, classificationProblemData.TrainingIndices)) {
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| 65 | tempModelParentNode.RemoveSubtree(i);
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[10273] | 66 |
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[14826] | 67 | var constantNode = new ConstantTreeNode(new Constant()) { Value = repValue };
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| 68 | tempModelParentNode.InsertSubtree(i, constantNode);
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[8409] | 69 |
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[14826] | 70 | var dataset = classificationProblemData.Dataset;
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| 71 | var targetClassValues = dataset.GetDoubleValues(classificationProblemData.TargetVariable, rows);
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| 72 | var estimatedClassValues = tempModel.GetEstimatedClassValues(dataset, rows);
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| 73 | OnlineCalculatorError errorState;
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| 74 | newQualityForImpactsCalculation = OnlineAccuracyCalculator.Calculate(targetClassValues, estimatedClassValues,
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| 75 | out errorState);
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| 76 | if (errorState != OnlineCalculatorError.None) newQualityForImpactsCalculation = 0.0;
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| 77 |
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| 78 | impactValue = qualityForImpactsCalculation - newQualityForImpactsCalculation;
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| 79 |
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| 80 | if (impactValue < bestImpactValue) {
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| 81 | bestImpactValue = impactValue;
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| 82 | bestReplacementValue = repValue;
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| 83 | }
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| 84 | }
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| 85 | replacementValue = bestReplacementValue;
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| 86 | impactValue = bestImpactValue;
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[8409] | 87 | }
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[12720] | 88 |
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| 89 | public static double CalculateQualityForImpacts(ISymbolicClassificationModel model, IClassificationProblemData problemData, IEnumerable<int> rows) {
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| 90 | OnlineCalculatorError errorState;
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| 91 | var dataset = problemData.Dataset;
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| 92 | var targetClassValues = dataset.GetDoubleValues(problemData.TargetVariable, rows);
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| 93 | var originalClassValues = model.GetEstimatedClassValues(dataset, rows);
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| 94 | var qualityForImpactsCalculation = OnlineAccuracyCalculator.Calculate(targetClassValues, originalClassValues, out errorState);
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| 95 | if (errorState != OnlineCalculatorError.None) qualityForImpactsCalculation = 0.0;
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| 96 |
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| 97 | return qualityForImpactsCalculation;
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| 98 | }
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[8409] | 99 | }
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| 100 | }
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