1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2019 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 HEAL.Fossil;
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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 regression data analysis solution that supports confidence estimates
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30 | /// </summary>
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31 | [StorableType("C2D0DE07-E8F0-4850-AAF3-E2885EC1DDB6")]
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32 | public class ConfidenceRegressionSolution : RegressionSolution, IConfidenceRegressionSolution {
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33 | protected readonly Dictionary<int, double> varianceEvaluationCache;
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34 |
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35 | public new IConfidenceRegressionModel Model {
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36 | get { return (IConfidenceRegressionModel)base.Model; }
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37 | set { base.Model = value; }
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38 | }
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39 |
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40 | [StorableConstructor]
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41 | protected ConfidenceRegressionSolution(StorableConstructorFlag _) : base(_) {
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42 | varianceEvaluationCache = new Dictionary<int, double>();
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43 | }
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44 | protected ConfidenceRegressionSolution(ConfidenceRegressionSolution original, Cloner cloner)
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45 | : base(original, cloner) {
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46 | varianceEvaluationCache = new Dictionary<int, double>(original.varianceEvaluationCache);
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47 | }
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48 | public ConfidenceRegressionSolution(IConfidenceRegressionModel model, IRegressionProblemData problemData)
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49 | : base(model, problemData) {
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50 | varianceEvaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
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51 | }
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52 |
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53 | public override IDeepCloneable Clone(Cloner cloner) {
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54 | return new ConfidenceRegressionSolution(this, cloner);
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55 | }
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56 |
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57 | public IEnumerable<double> EstimatedVariances {
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58 | get { return GetEstimatedVariances(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
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59 | }
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60 | public IEnumerable<double> EstimatedTrainingVariances {
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61 | get { return GetEstimatedVariances(ProblemData.TrainingIndices); }
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62 | }
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63 | public IEnumerable<double> EstimatedTestVariances {
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64 | get { return GetEstimatedVariances(ProblemData.TestIndices); }
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65 | }
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66 |
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67 | public IEnumerable<double> GetEstimatedVariances(IEnumerable<int> rows) {
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68 | var rowsToEvaluate = rows.Except(varianceEvaluationCache.Keys);
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69 | var rowsEnumerator = rowsToEvaluate.GetEnumerator();
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70 | var valuesEnumerator = Model.GetEstimatedVariances(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
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71 |
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72 | while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
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73 | varianceEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
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74 | }
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75 |
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76 | return rows.Select(row => varianceEvaluationCache[row]);
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77 | }
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78 |
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79 | protected override void OnProblemDataChanged() {
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80 | varianceEvaluationCache.Clear();
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81 | base.OnProblemDataChanged();
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82 | }
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83 |
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84 | protected override void OnModelChanged() {
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85 | varianceEvaluationCache.Clear();
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86 | base.OnModelChanged();
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87 | }
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88 | }
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89 | } |
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