1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2013 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 HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Parameters;
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27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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28 |
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29 | namespace HeuristicLab.Problems.DataAnalysis {
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30 | [StorableClass]
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31 | [Item("RegressionEnsembleProblemData", "Represents an item containing all data defining a regression problem.")]
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32 | public sealed class RegressionEnsembleProblemData : RegressionProblemData {
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33 |
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34 | public override bool IsTrainingSample(int index) {
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35 | return index >= 0 && index < Dataset.Rows &&
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36 | TrainingPartition.Start <= index && index < TrainingPartition.End;
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37 | }
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38 |
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39 | public override bool IsTestSample(int index) {
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40 | return index >= 0 && index < Dataset.Rows &&
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41 | TestPartition.Start <= index && index < TestPartition.End;
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42 | }
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43 |
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44 | private static readonly RegressionEnsembleProblemData emptyProblemData;
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45 | public new static RegressionEnsembleProblemData EmptyProblemData {
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46 | get { return emptyProblemData; }
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47 | }
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48 | static RegressionEnsembleProblemData() {
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49 | var problemData = new RegressionEnsembleProblemData();
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50 | problemData.Parameters.Clear();
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51 | problemData.Name = "Empty Regression ProblemData";
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52 | problemData.Description = "This ProblemData acts as place holder before the correct problem data is loaded.";
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53 | problemData.isEmpty = true;
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54 |
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55 | problemData.Parameters.Add(new FixedValueParameter<Dataset>(DatasetParameterName, "", new Dataset()));
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56 | problemData.Parameters.Add(new FixedValueParameter<ReadOnlyCheckedItemList<StringValue>>(InputVariablesParameterName, ""));
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57 | problemData.Parameters.Add(new FixedValueParameter<IntRange>(TrainingPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly()));
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58 | problemData.Parameters.Add(new FixedValueParameter<IntRange>(TestPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly()));
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59 | problemData.Parameters.Add(new ConstrainedValueParameter<StringValue>(TargetVariableParameterName, new ItemSet<StringValue>()));
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60 | emptyProblemData = problemData;
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61 | }
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62 |
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63 | [StorableConstructor]
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64 | private RegressionEnsembleProblemData(bool deserializing) : base(deserializing) { }
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65 | private RegressionEnsembleProblemData(RegressionEnsembleProblemData original, Cloner cloner) : base(original, cloner) { }
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66 | public override IDeepCloneable Clone(Cloner cloner) {
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67 | if (this == emptyProblemData) return emptyProblemData;
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68 | return new RegressionEnsembleProblemData(this, cloner);
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69 | }
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70 |
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71 | public RegressionEnsembleProblemData() : base() { }
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72 | public RegressionEnsembleProblemData(IRegressionProblemData regressionProblemData)
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73 | : base(regressionProblemData.Dataset, regressionProblemData.AllowedInputVariables, regressionProblemData.TargetVariable) {
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74 | TrainingPartition.Start = regressionProblemData.TrainingPartition.Start;
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75 | TrainingPartition.End = regressionProblemData.TrainingPartition.End;
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76 | TestPartition.Start = regressionProblemData.TestPartition.Start;
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77 | TestPartition.End = regressionProblemData.TestPartition.End;
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78 | }
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79 | public RegressionEnsembleProblemData(Dataset dataset, IEnumerable<string> allowedInputVariables, string targetVariable)
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80 | : base(dataset, allowedInputVariables, targetVariable) {
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81 | }
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82 | }
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83 | }
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