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.Collections.Generic;
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23 | using System.Linq;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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26 |
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27 | namespace HeuristicLab.Problems.DataAnalysis {
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28 | /// <summary>
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29 | /// Represents a classification data analysis solution
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30 | /// </summary>
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31 | [StorableClass]
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32 | public abstract class ClassificationSolution : ClassificationSolutionBase {
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33 | protected readonly Dictionary<int, double> evaluationCache;
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34 |
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35 | [StorableConstructor]
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36 | protected ClassificationSolution(bool deserializing)
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37 | : base(deserializing) {
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38 | evaluationCache = new Dictionary<int, double>();
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39 | }
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40 | protected ClassificationSolution(ClassificationSolution original, Cloner cloner)
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41 | : base(original, cloner) {
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42 | evaluationCache = new Dictionary<int, double>(original.evaluationCache);
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43 | }
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44 | public ClassificationSolution(IClassificationModel model, IClassificationProblemData problemData)
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45 | : base(model, problemData) {
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46 | evaluationCache = new Dictionary<int, double>();
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47 | }
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48 |
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49 | public override IEnumerable<double> EstimatedClassValues {
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50 | get { return GetEstimatedClassValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
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51 | }
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52 | public override IEnumerable<double> EstimatedTrainingClassValues {
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53 | get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
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54 | }
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55 | public override IEnumerable<double> EstimatedTestClassValues {
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56 | get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
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57 | }
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58 |
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59 | public override IEnumerable<double> GetEstimatedClassValues(IEnumerable<int> rows) {
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60 | var rowsToEvaluate = rows.Except(evaluationCache.Keys);
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61 | var rowsEnumerator = rowsToEvaluate.GetEnumerator();
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62 | var valuesEnumerator = Model.GetEstimatedClassValues(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
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63 |
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64 | while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
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65 | evaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
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66 | }
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67 |
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68 | return rows.Select(row => evaluationCache[row]);
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69 | }
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70 |
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71 | protected override void OnProblemDataChanged() {
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72 | evaluationCache.Clear();
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73 | base.OnProblemDataChanged();
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74 | }
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75 |
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76 | protected override void OnModelChanged() {
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77 | evaluationCache.Clear();
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78 | base.OnModelChanged();
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79 | }
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80 | }
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81 | }
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