[8409] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17246] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8409] | 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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| 22 | using System.Collections.Generic;
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[14826] | 23 | using System.Linq;
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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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[16662] | 27 | using HEAL.Attic;
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[8409] | 28 |
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| 29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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[16662] | 30 | [StorableType("E725708A-508E-47DC-B667-DAA569FD1DC2")]
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[10469] | 31 | [Item("SymbolicDataAnalysisSolutionImpactValuesCalculator", "Calculates the impact values and replacements values for symbolic expression tree nodes.")]
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| 32 | public abstract class SymbolicDataAnalysisSolutionImpactValuesCalculator : Item, ISymbolicDataAnalysisSolutionImpactValuesCalculator {
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| 33 | protected SymbolicDataAnalysisSolutionImpactValuesCalculator() { }
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| 34 | protected SymbolicDataAnalysisSolutionImpactValuesCalculator(SymbolicDataAnalysisSolutionImpactValuesCalculator original, Cloner cloner)
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| 35 | : base(original, cloner) { }
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| 36 | [StorableConstructor]
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[16662] | 37 | protected SymbolicDataAnalysisSolutionImpactValuesCalculator(StorableConstructorFlag _) : base(_) { }
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[8409] | 38 |
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[15371] | 39 | public virtual void CalculateImpactAndReplacementValues(ISymbolicDataAnalysisModel model, ISymbolicExpressionTreeNode node, IDataAnalysisProblemData problemData, IEnumerable<int> rows,
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| 40 | out double impactValue, out double replacementValue, out double newQualityForImpactsCalculation,
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| 41 | double qualityForImpactsCalculation = double.NaN) {
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| 42 |
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| 43 | var cloner = new Cloner();
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| 44 | var tempModel = cloner.Clone(model);
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[15871] | 45 |
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| 46 | if (double.IsNaN(qualityForImpactsCalculation)) {
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| 47 | qualityForImpactsCalculation = CalculateQualityForImpacts(tempModel, problemData, rows);
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| 48 | }
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| 49 |
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[15371] | 50 | var tempModelNode = (ISymbolicExpressionTreeNode)cloner.GetClone(node);
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| 51 | var tempModelParentNode = tempModelNode.Parent;
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| 52 | int i = tempModelParentNode.IndexOfSubtree(tempModelNode);
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| 53 |
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| 54 | double bestReplacementValue = 0.0;
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| 55 | double bestImpactValue = double.PositiveInfinity;
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| 56 | newQualityForImpactsCalculation = qualityForImpactsCalculation; // initialize
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| 57 | // try the potentially reasonable replacement values and use the best one
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[15871] | 58 | foreach (var repValue in CalculateReplacementValues(node, model.SymbolicExpressionTree, model.Interpreter, problemData.Dataset, rows)) {
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[15371] | 59 | tempModelParentNode.RemoveSubtree(i);
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| 60 |
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| 61 | var constantNode = new ConstantTreeNode(new Constant()) { Value = repValue };
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| 62 | tempModelParentNode.InsertSubtree(i, constantNode);
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| 63 |
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| 64 | newQualityForImpactsCalculation = CalculateQualityForImpacts(tempModel, problemData, rows);
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| 65 |
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| 66 | impactValue = qualityForImpactsCalculation - newQualityForImpactsCalculation;
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| 67 | if (impactValue < bestImpactValue) {
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| 68 | bestImpactValue = impactValue;
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| 69 | bestReplacementValue = repValue;
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| 70 | }
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| 71 | }
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| 72 |
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| 73 | replacementValue = bestReplacementValue;
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| 74 | impactValue = bestImpactValue;
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| 75 | }
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| 76 |
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| 77 | protected abstract double CalculateQualityForImpacts(ISymbolicDataAnalysisModel model, IDataAnalysisProblemData problemData, IEnumerable<int> rows);
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| 78 |
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[14826] | 79 | protected IEnumerable<double> CalculateReplacementValues(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
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[12509] | 80 | IDataset dataset, IEnumerable<int> rows) {
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[8946] | 81 | //optimization: constant nodes return always the same value
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| 82 | ConstantTreeNode constantNode = node as ConstantTreeNode;
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[14826] | 83 | BinaryFactorVariableTreeNode binaryFactorNode = node as BinaryFactorVariableTreeNode;
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| 84 | FactorVariableTreeNode factorNode = node as FactorVariableTreeNode;
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| 85 | if (constantNode != null) {
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| 86 | yield return constantNode.Value;
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| 87 | } else if (binaryFactorNode != null) {
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| 88 | // valid replacements are either all off or all on
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| 89 | yield return 0;
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| 90 | yield return 1;
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| 91 | } else if (factorNode != null) {
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| 92 | foreach (var w in factorNode.Weights) yield return w;
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| 93 | yield return 0.0;
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| 94 | } else {
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| 95 | var rootSymbol = new ProgramRootSymbol().CreateTreeNode();
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| 96 | var startSymbol = new StartSymbol().CreateTreeNode();
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| 97 | rootSymbol.AddSubtree(startSymbol);
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| 98 | startSymbol.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
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[8409] | 99 |
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[14826] | 100 | var tempTree = new SymbolicExpressionTree(rootSymbol);
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| 101 | // clone ADFs of source tree
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| 102 | for (int i = 1; i < sourceTree.Root.SubtreeCount; i++) {
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| 103 | tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
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| 104 | }
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| 105 | yield return interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Median();
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| 106 | yield return interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Average(); // TODO perf
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[8946] | 107 | }
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[8409] | 108 | }
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| 109 | }
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| 110 | }
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