1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Views;
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28 |
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29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views {
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30 | public abstract partial class InteractiveSymbolicClassificationSolutionSimplifierViewBase : InteractiveSymbolicDataAnalysisSolutionSimplifierView {
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31 | private readonly SymbolicClassificationSolutionImpactValuesCalculator calculator;
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32 |
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33 | public new ISymbolicClassificationSolution Content {
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34 | get { return (ISymbolicClassificationSolution)base.Content; }
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35 | set { base.Content = value; }
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36 | }
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37 |
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38 | public InteractiveSymbolicClassificationSolutionSimplifierViewBase()
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39 | : base() {
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40 | InitializeComponent();
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41 | this.Caption = "Interactive Classification Solution Simplifier";
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42 |
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43 | calculator = new SymbolicClassificationSolutionImpactValuesCalculator();
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44 | }
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45 |
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46 | /// <summary>
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47 | /// It is necessary to create new models of an unknown type with new trees in the simplifier.
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48 | /// For this purpose the cloner is used by registering the new tree as already cloned object and invoking the clone mechanism.
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49 | /// This results in a new model of the same type as the old one with an exchanged tree.
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50 | /// </summary>
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51 | /// <param name="tree">The new tree that should be included in the new object</param>
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52 | /// <returns></returns>
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53 | protected ISymbolicClassificationModel CreateModel(ISymbolicExpressionTree tree) {
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54 | var cloner = new Cloner();
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55 | cloner.RegisterClonedObject(Content.Model.SymbolicExpressionTree, tree);
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56 |
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57 | var model = (ISymbolicClassificationModel)Content.Model.Clone(cloner);
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58 | model.RecalculateModelParameters(Content.ProblemData, Content.ProblemData.TrainingIndices);
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59 | return model;
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60 | }
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61 |
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62 | protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateReplacementValues(ISymbolicExpressionTree tree) {
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63 | return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary(
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64 | n => n,
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65 | n => calculator.CalculateReplacementValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices)
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66 | );
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67 | }
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68 |
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69 | protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateImpactValues(ISymbolicExpressionTree tree) {
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70 | return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary(
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71 | n => n,
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72 | n => calculator.CalculateImpactValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices, Content.TrainingAccuracy)
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73 | );
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74 | }
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75 |
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76 | protected override void btnOptimizeConstants_Click(object sender, EventArgs e) {
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77 |
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78 | }
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79 | }
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80 | }
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