[5816] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5816] | 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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[6588] | 22 | using System;
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[5816] | 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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[6612] | 25 | using HeuristicLab.Collections;
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[5816] | 26 | using HeuristicLab.Common;
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| 27 | using HeuristicLab.Core;
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[6588] | 28 | using HeuristicLab.Data;
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[5816] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 |
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| 31 | namespace HeuristicLab.Problems.DataAnalysis {
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| 32 | /// <summary>
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| 33 | /// Represents regression solutions that contain an ensemble of multiple regression models
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| 34 | /// </summary>
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| 35 | [StorableClass]
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| 36 | [Item("Regression Ensemble Solution", "A regression solution that contains an ensemble of multiple regression models")]
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[12504] | 37 | [Creatable(CreatableAttribute.Categories.DataAnalysisEnsembles, Priority = 100)]
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[8724] | 38 | public sealed class RegressionEnsembleSolution : RegressionSolutionBase, IRegressionEnsembleSolution {
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[8167] | 39 | private readonly Dictionary<int, double> trainingEvaluationCache = new Dictionary<int, double>();
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| 40 | private readonly Dictionary<int, double> testEvaluationCache = new Dictionary<int, double>();
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[8724] | 41 | private readonly Dictionary<int, double> evaluationCache = new Dictionary<int, double>();
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[8151] | 42 |
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[5816] | 43 | public new IRegressionEnsembleModel Model {
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| 44 | get { return (IRegressionEnsembleModel)base.Model; }
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| 45 | }
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| 46 |
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[6666] | 47 | public new RegressionEnsembleProblemData ProblemData {
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| 48 | get { return (RegressionEnsembleProblemData)base.ProblemData; }
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| 49 | set { base.ProblemData = value; }
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| 50 | }
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| 51 |
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[12816] | 52 | [Storable]
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[6612] | 53 | private readonly ItemCollection<IRegressionSolution> regressionSolutions;
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| 54 | public IItemCollection<IRegressionSolution> RegressionSolutions {
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| 55 | get { return regressionSolutions; }
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| 56 | }
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| 57 |
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[5816] | 58 | [Storable]
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[8152] | 59 | private readonly Dictionary<IRegressionModel, IntRange> trainingPartitions;
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[5816] | 60 | [Storable]
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[8152] | 61 | private readonly Dictionary<IRegressionModel, IntRange> testPartitions;
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[5816] | 62 |
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| 63 | [StorableConstructor]
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[6612] | 64 | private RegressionEnsembleSolution(bool deserializing)
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| 65 | : base(deserializing) {
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| 66 | regressionSolutions = new ItemCollection<IRegressionSolution>();
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| 67 | }
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| 68 | [StorableHook(HookType.AfterDeserialization)]
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| 69 | private void AfterDeserialization() {
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[12816] | 70 | if (!regressionSolutions.Any()) {
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| 71 | foreach (var model in Model.Models) {
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| 72 | IRegressionProblemData problemData = (IRegressionProblemData)ProblemData.Clone();
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| 73 | problemData.TrainingPartition.Start = trainingPartitions[model].Start;
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| 74 | problemData.TrainingPartition.End = trainingPartitions[model].End;
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| 75 | problemData.TestPartition.Start = testPartitions[model].Start;
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| 76 | problemData.TestPartition.End = testPartitions[model].End;
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[6612] | 77 |
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[12816] | 78 | regressionSolutions.Add(model.CreateRegressionSolution(problemData));
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| 79 | }
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[6612] | 80 | }
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[13704] | 81 |
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| 82 | RegisterModelEvents();
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[6612] | 83 | RegisterRegressionSolutionsEventHandler();
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| 84 | }
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| 85 |
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[6592] | 86 | private RegressionEnsembleSolution(RegressionEnsembleSolution original, Cloner cloner)
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[5816] | 87 | : base(original, cloner) {
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[6239] | 88 | trainingPartitions = new Dictionary<IRegressionModel, IntRange>();
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| 89 | testPartitions = new Dictionary<IRegressionModel, IntRange>();
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[6302] | 90 | foreach (var pair in original.trainingPartitions) {
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| 91 | trainingPartitions[cloner.Clone(pair.Key)] = cloner.Clone(pair.Value);
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[6239] | 92 | }
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[6302] | 93 | foreach (var pair in original.testPartitions) {
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| 94 | testPartitions[cloner.Clone(pair.Key)] = cloner.Clone(pair.Value);
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| 95 | }
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[6612] | 96 |
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[13698] | 97 | evaluationCache = new Dictionary<int, double>(original.ProblemData.Dataset.Rows);
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[8174] | 98 | trainingEvaluationCache = new Dictionary<int, double>(original.ProblemData.TrainingIndices.Count());
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| 99 | testEvaluationCache = new Dictionary<int, double>(original.ProblemData.TestIndices.Count());
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| 100 |
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[6612] | 101 | regressionSolutions = cloner.Clone(original.regressionSolutions);
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[13704] | 102 | RegisterModelEvents();
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[6612] | 103 | RegisterRegressionSolutionsEventHandler();
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[5816] | 104 | }
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[6239] | 105 |
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[6666] | 106 | public RegressionEnsembleSolution()
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| 107 | : base(new RegressionEnsembleModel(), RegressionEnsembleProblemData.EmptyProblemData) {
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| 108 | trainingPartitions = new Dictionary<IRegressionModel, IntRange>();
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| 109 | testPartitions = new Dictionary<IRegressionModel, IntRange>();
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| 110 | regressionSolutions = new ItemCollection<IRegressionSolution>();
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| 111 |
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[13704] | 112 | RegisterModelEvents();
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[6666] | 113 | RegisterRegressionSolutionsEventHandler();
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| 114 | }
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| 115 |
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[7738] | 116 | public RegressionEnsembleSolution(IRegressionProblemData problemData)
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[13698] | 117 | : this(new RegressionEnsembleModel(), problemData) {
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[7738] | 118 | }
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| 119 |
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[13698] | 120 | public RegressionEnsembleSolution(IRegressionEnsembleModel model, IRegressionProblemData problemData)
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| 121 | : base(model, new RegressionEnsembleProblemData(problemData)) {
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| 122 | trainingPartitions = new Dictionary<IRegressionModel, IntRange>();
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| 123 | testPartitions = new Dictionary<IRegressionModel, IntRange>();
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| 124 | regressionSolutions = new ItemCollection<IRegressionSolution>();
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[5816] | 125 |
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[13698] | 126 | evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
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[8174] | 127 | trainingEvaluationCache = new Dictionary<int, double>(problemData.TrainingIndices.Count());
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| 128 | testEvaluationCache = new Dictionary<int, double>(problemData.TestIndices.Count());
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| 129 |
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[13702] | 130 |
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| 131 | var solutions = model.Models.Select(m => m.CreateRegressionSolution((IRegressionProblemData)problemData.Clone()));
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| 132 | foreach (var solution in solutions) {
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| 133 | regressionSolutions.Add(solution);
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| 134 | trainingPartitions.Add(solution.Model, solution.ProblemData.TrainingPartition);
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| 135 | testPartitions.Add(solution.Model, solution.ProblemData.TestPartition);
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| 136 | }
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| 137 |
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| 138 | RecalculateResults();
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[13704] | 139 | RegisterModelEvents();
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[6612] | 140 | RegisterRegressionSolutionsEventHandler();
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[5816] | 141 | }
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| 142 |
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[13698] | 143 |
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[5816] | 144 | public override IDeepCloneable Clone(Cloner cloner) {
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| 145 | return new RegressionEnsembleSolution(this, cloner);
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| 146 | }
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[13704] | 147 |
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| 148 | private void RegisterModelEvents() {
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| 149 | Model.Changed += Model_Changed;
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| 150 | }
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[6612] | 151 | private void RegisterRegressionSolutionsEventHandler() {
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| 152 | regressionSolutions.ItemsAdded += new CollectionItemsChangedEventHandler<IRegressionSolution>(regressionSolutions_ItemsAdded);
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| 153 | regressionSolutions.ItemsRemoved += new CollectionItemsChangedEventHandler<IRegressionSolution>(regressionSolutions_ItemsRemoved);
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| 154 | regressionSolutions.CollectionReset += new CollectionItemsChangedEventHandler<IRegressionSolution>(regressionSolutions_CollectionReset);
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| 155 | }
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[5816] | 156 |
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[6612] | 157 | #region Evaluation
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[8724] | 158 | public override IEnumerable<double> EstimatedValues {
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| 159 | get { return GetEstimatedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
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| 160 | }
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| 161 |
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[5816] | 162 | public override IEnumerable<double> EstimatedTrainingValues {
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[8152] | 163 | get {
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| 164 | var rows = ProblemData.TrainingIndices;
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[8167] | 165 | var rowsToEvaluate = rows.Except(trainingEvaluationCache.Keys);
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[13704] | 166 |
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[8152] | 167 | var rowsEnumerator = rowsToEvaluate.GetEnumerator();
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[13697] | 168 | var valuesEnumerator = Model.GetEstimatedValues(ProblemData.Dataset, rowsToEvaluate, (r, m) => RowIsTrainingForModel(r, m) && !RowIsTestForModel(r, m)).GetEnumerator();
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[8152] | 169 |
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| 170 | while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
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[8167] | 171 | trainingEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
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[8152] | 172 | }
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| 173 |
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[8167] | 174 | return rows.Select(row => trainingEvaluationCache[row]);
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[8152] | 175 | }
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[5816] | 176 | }
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| 177 |
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| 178 | public override IEnumerable<double> EstimatedTestValues {
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[8152] | 179 | get {
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| 180 | var rows = ProblemData.TestIndices;
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[8167] | 181 | var rowsToEvaluate = rows.Except(testEvaluationCache.Keys);
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[8152] | 182 | var rowsEnumerator = rowsToEvaluate.GetEnumerator();
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[13697] | 183 | var valuesEnumerator = Model.GetEstimatedValues(ProblemData.Dataset, rowsToEvaluate, RowIsTestForModel).GetEnumerator();
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[8152] | 184 |
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| 185 | while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
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[8167] | 186 | testEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
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[8152] | 187 | }
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| 188 |
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[8167] | 189 | return rows.Select(row => testEvaluationCache[row]);
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[8152] | 190 | }
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[8151] | 191 | }
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[6254] | 192 | private bool RowIsTrainingForModel(int currentRow, IRegressionModel model) {
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| 193 | return trainingPartitions == null || !trainingPartitions.ContainsKey(model) ||
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| 194 | (trainingPartitions[model].Start <= currentRow && currentRow < trainingPartitions[model].End);
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| 195 | }
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| 196 | private bool RowIsTestForModel(int currentRow, IRegressionModel model) {
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| 197 | return testPartitions == null || !testPartitions.ContainsKey(model) ||
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| 198 | (testPartitions[model].Start <= currentRow && currentRow < testPartitions[model].End);
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| 199 | }
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| 200 |
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[5816] | 201 | public override IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows) {
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[8167] | 202 | var rowsToEvaluate = rows.Except(evaluationCache.Keys);
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[8152] | 203 | var rowsEnumerator = rowsToEvaluate.GetEnumerator();
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[13697] | 204 | var valuesEnumerator = Model.GetEstimatedValues(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
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[8152] | 205 |
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| 206 | while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
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[8167] | 207 | evaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
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[8152] | 208 | }
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| 209 |
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[8167] | 210 | return rows.Select(row => evaluationCache[row]);
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[5816] | 211 | }
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| 212 |
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[13697] | 213 | public IEnumerable<IEnumerable<double>> GetEstimatedValueVectors(IEnumerable<int> rows) {
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| 214 | return Model.GetEstimatedValueVectors(ProblemData.Dataset, rows);
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[5816] | 215 | }
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[6612] | 216 | #endregion
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[6520] | 217 |
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[6666] | 218 | protected override void OnProblemDataChanged() {
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[8167] | 219 | trainingEvaluationCache.Clear();
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| 220 | testEvaluationCache.Clear();
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| 221 | evaluationCache.Clear();
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[6666] | 222 | IRegressionProblemData problemData = new RegressionProblemData(ProblemData.Dataset,
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| 223 | ProblemData.AllowedInputVariables,
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| 224 | ProblemData.TargetVariable);
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| 225 | problemData.TrainingPartition.Start = ProblemData.TrainingPartition.Start;
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| 226 | problemData.TrainingPartition.End = ProblemData.TrainingPartition.End;
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| 227 | problemData.TestPartition.Start = ProblemData.TestPartition.Start;
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| 228 | problemData.TestPartition.End = ProblemData.TestPartition.End;
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| 229 |
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| 230 | foreach (var solution in RegressionSolutions) {
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| 231 | if (solution is RegressionEnsembleSolution)
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| 232 | solution.ProblemData = ProblemData;
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| 233 | else
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| 234 | solution.ProblemData = problemData;
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| 235 | }
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| 236 | foreach (var trainingPartition in trainingPartitions.Values) {
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| 237 | trainingPartition.Start = ProblemData.TrainingPartition.Start;
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| 238 | trainingPartition.End = ProblemData.TrainingPartition.End;
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| 239 | }
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| 240 | foreach (var testPartition in testPartitions.Values) {
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| 241 | testPartition.Start = ProblemData.TestPartition.Start;
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| 242 | testPartition.End = ProblemData.TestPartition.End;
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| 243 | }
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| 244 |
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| 245 | base.OnProblemDataChanged();
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| 246 | }
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| 247 |
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[13704] | 248 | private void Model_Changed(object sender, EventArgs e) {
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| 249 | var modelSet = new HashSet<IRegressionModel>(Model.Models);
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| 250 | foreach (var model in Model.Models) {
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| 251 | if (!trainingPartitions.ContainsKey(model)) trainingPartitions.Add(model, ProblemData.TrainingPartition);
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| 252 | if (!testPartitions.ContainsKey(model)) testPartitions.Add(model, ProblemData.TrainingPartition);
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| 253 | }
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| 254 | foreach (var model in trainingPartitions.Keys) {
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| 255 | if (modelSet.Contains(model)) continue;
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| 256 | trainingPartitions.Remove(model);
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| 257 | testPartitions.Remove(model);
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| 258 | }
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[8152] | 259 |
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[8167] | 260 | trainingEvaluationCache.Clear();
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| 261 | testEvaluationCache.Clear();
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| 262 | evaluationCache.Clear();
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[13704] | 263 |
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| 264 | OnModelChanged();
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[6612] | 265 | }
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[13704] | 266 |
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| 267 | public void AddRegressionSolutions(IEnumerable<IRegressionSolution> solutions) {
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| 268 | regressionSolutions.AddRange(solutions);
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| 269 | }
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[6612] | 270 | public void RemoveRegressionSolutions(IEnumerable<IRegressionSolution> solutions) {
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| 271 | regressionSolutions.RemoveRange(solutions);
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| 272 | }
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[6520] | 273 |
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[6612] | 274 | private void regressionSolutions_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IRegressionSolution> e) {
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[13704] | 275 | foreach (var solution in e.Items) {
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| 276 | trainingPartitions.Add(solution.Model, solution.ProblemData.TrainingPartition);
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| 277 | testPartitions.Add(solution.Model, solution.ProblemData.TestPartition);
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| 278 | }
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| 279 | Model.AddRange(e.Items.Select(s => s.Model));
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[6520] | 280 | }
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[6612] | 281 | private void regressionSolutions_ItemsRemoved(object sender, CollectionItemsChangedEventArgs<IRegressionSolution> e) {
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[13704] | 282 | foreach (var solution in e.Items) {
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| 283 | trainingPartitions.Remove(solution.Model);
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| 284 | testPartitions.Remove(solution.Model);
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| 285 | }
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| 286 | Model.RemoveRange(e.Items.Select(s => s.Model));
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[6612] | 287 | }
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| 288 | private void regressionSolutions_CollectionReset(object sender, CollectionItemsChangedEventArgs<IRegressionSolution> e) {
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[13704] | 289 | foreach (var solution in e.OldItems) {
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| 290 | trainingPartitions.Remove(solution.Model);
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| 291 | testPartitions.Remove(solution.Model);
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| 292 | }
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| 293 | Model.RemoveRange(e.OldItems.Select(s => s.Model));
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[6520] | 294 |
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[13704] | 295 | foreach (var solution in e.Items) {
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| 296 | trainingPartitions.Add(solution.Model, solution.ProblemData.TrainingPartition);
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| 297 | testPartitions.Add(solution.Model, solution.ProblemData.TestPartition);
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| 298 | }
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| 299 | Model.AddRange(e.Items.Select(s => s.Model));
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[6612] | 300 | }
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[5816] | 301 | }
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| 302 | }
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