[5816] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2011 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.Core;
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| 26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[6239] | 27 | using HeuristicLab.Data;
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| 28 | using System;
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[5816] | 29 |
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| 30 | namespace HeuristicLab.Problems.DataAnalysis {
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| 31 | /// <summary>
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| 32 | /// Represents classification solutions that contain an ensemble of multiple classification models
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| 33 | /// </summary>
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| 34 | [StorableClass]
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| 35 | [Item("Classification Ensemble Solution", "A classification solution that contains an ensemble of multiple classification models")]
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| 36 | // [Creatable("Data Analysis")]
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[6239] | 37 | public class ClassificationEnsembleSolution : ClassificationSolution, IClassificationEnsembleSolution {
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[5816] | 38 |
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[6239] | 39 | public new IClassificationEnsembleModel Model {
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| 40 | set { base.Model = value; }
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| 41 | get { return (IClassificationEnsembleModel)base.Model; }
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| 42 | }
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| 43 |
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[5816] | 44 | [Storable]
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[6239] | 45 | private Dictionary<IClassificationModel, IntRange> trainingPartitions;
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| 46 | [Storable]
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| 47 | private Dictionary<IClassificationModel, IntRange> testPartitions;
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| 48 |
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| 49 |
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[5816] | 50 | [StorableConstructor]
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| 51 | protected ClassificationEnsembleSolution(bool deserializing) : base(deserializing) { }
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| 52 | protected ClassificationEnsembleSolution(ClassificationEnsembleSolution original, Cloner cloner)
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| 53 | : base(original, cloner) {
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[6239] | 54 | trainingPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 55 | testPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 56 | foreach (var model in Model.Models) {
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| 57 | trainingPartitions[model] = (IntRange)ProblemData.TrainingPartition.Clone();
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| 58 | testPartitions[model] = (IntRange)ProblemData.TestPartition.Clone();
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| 59 | }
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| 60 | RecalculateResults();
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[5816] | 61 | }
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[6239] | 62 | public ClassificationEnsembleSolution(IEnumerable<IClassificationModel> models, IClassificationProblemData problemData)
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| 63 | : base(new ClassificationEnsembleModel(models), new ClassificationEnsembleProblemData(problemData)) {
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[5816] | 64 | this.name = ItemName;
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| 65 | this.description = ItemDescription;
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[6239] | 66 | trainingPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 67 | testPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 68 | foreach (var model in models) {
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| 69 | trainingPartitions[model] = (IntRange)problemData.TrainingPartition.Clone();
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| 70 | testPartitions[model] = (IntRange)problemData.TestPartition.Clone();
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| 71 | }
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| 72 | RecalculateResults();
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[5816] | 73 | }
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| 74 |
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[6239] | 75 | public ClassificationEnsembleSolution(IEnumerable<IClassificationModel> models, IClassificationProblemData problemData, IEnumerable<IntRange> trainingPartitions, IEnumerable<IntRange> testPartitions)
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| 76 | : base(new ClassificationEnsembleModel(models), new ClassificationEnsembleProblemData(problemData)) {
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| 77 | this.trainingPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 78 | this.testPartitions = new Dictionary<IClassificationModel, IntRange>();
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| 79 | var modelEnumerator = models.GetEnumerator();
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| 80 | var trainingPartitionEnumerator = trainingPartitions.GetEnumerator();
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| 81 | var testPartitionEnumerator = testPartitions.GetEnumerator();
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| 82 | while (modelEnumerator.MoveNext() & trainingPartitionEnumerator.MoveNext() & testPartitionEnumerator.MoveNext()) {
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| 83 | this.trainingPartitions[modelEnumerator.Current] = (IntRange)trainingPartitionEnumerator.Current.Clone();
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| 84 | this.testPartitions[modelEnumerator.Current] = (IntRange)testPartitionEnumerator.Current.Clone();
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| 85 | }
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| 86 | if (modelEnumerator.MoveNext() | trainingPartitionEnumerator.MoveNext() | testPartitionEnumerator.MoveNext()) {
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| 87 | throw new ArgumentException();
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| 88 | }
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| 89 | RecalculateResults();
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| 90 | }
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| 91 |
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[5816] | 92 | public override IDeepCloneable Clone(Cloner cloner) {
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| 93 | return new ClassificationEnsembleSolution(this, cloner);
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| 94 | }
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| 95 |
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[6239] | 96 | public override IEnumerable<double> EstimatedTrainingClassValues {
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| 97 | get {
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| 98 | var rows = ProblemData.TrainingIndizes;
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| 99 | var estimatedValuesEnumerators = (from model in Model.Models
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| 100 | select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
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| 101 | .ToList();
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| 102 | var rowsEnumerator = rows.GetEnumerator();
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| 103 | // aggregate to make sure that MoveNext is called for all enumerators
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| 104 | while (rowsEnumerator.MoveNext() & estimatedValuesEnumerators.Select(en => en.EstimatedValuesEnumerator.MoveNext()).Aggregate(true, (acc, b) => acc & b)) {
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| 105 | int currentRow = rowsEnumerator.Current;
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[5816] | 106 |
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[6239] | 107 | var selectedEnumerators = from pair in estimatedValuesEnumerators
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| 108 | where trainingPartitions == null || !trainingPartitions.ContainsKey(pair.Model) ||
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| 109 | (trainingPartitions[pair.Model].Start <= currentRow && currentRow < trainingPartitions[pair.Model].End)
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| 110 | select pair.EstimatedValuesEnumerator;
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| 111 | yield return AggregateEstimatedClassValues(selectedEnumerators.Select(x => x.Current));
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| 112 | }
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| 113 | }
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| 114 | }
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| 115 |
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| 116 | public override IEnumerable<double> EstimatedTestClassValues {
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| 117 | get {
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| 118 | var rows = ProblemData.TestIndizes;
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| 119 | var estimatedValuesEnumerators = (from model in Model.Models
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| 120 | select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
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| 121 | .ToList();
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| 122 | var rowsEnumerator = ProblemData.TestIndizes.GetEnumerator();
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| 123 | // aggregate to make sure that MoveNext is called for all enumerators
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| 124 | while (rowsEnumerator.MoveNext() & estimatedValuesEnumerators.Select(en => en.EstimatedValuesEnumerator.MoveNext()).Aggregate(true, (acc, b) => acc & b)) {
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| 125 | int currentRow = rowsEnumerator.Current;
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| 126 |
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| 127 | var selectedEnumerators = from pair in estimatedValuesEnumerators
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| 128 | where testPartitions == null || !testPartitions.ContainsKey(pair.Model) ||
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| 129 | (testPartitions[pair.Model].Start <= currentRow && currentRow < testPartitions[pair.Model].End)
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| 130 | select pair.EstimatedValuesEnumerator;
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| 131 |
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| 132 | yield return AggregateEstimatedClassValues(selectedEnumerators.Select(x => x.Current));
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| 133 | }
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| 134 | }
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| 135 | }
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| 136 |
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| 137 | public override IEnumerable<double> GetEstimatedClassValues(IEnumerable<int> rows) {
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| 138 | return from xs in GetEstimatedClassValueVectors(ProblemData.Dataset, rows)
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| 139 | select AggregateEstimatedClassValues(xs);
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| 140 | }
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| 141 |
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[5816] | 142 | public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows) {
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[6239] | 143 | var estimatedValuesEnumerators = (from model in Model.Models
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[5816] | 144 | select model.GetEstimatedClassValues(dataset, rows).GetEnumerator())
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| 145 | .ToList();
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| 146 |
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| 147 | while (estimatedValuesEnumerators.All(en => en.MoveNext())) {
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| 148 | yield return from enumerator in estimatedValuesEnumerators
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| 149 | select enumerator.Current;
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| 150 | }
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| 151 | }
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| 152 |
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[6239] | 153 | private double AggregateEstimatedClassValues(IEnumerable<double> estimatedClassValues) {
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| 154 | return estimatedClassValues
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| 155 | .GroupBy(x => x)
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| 156 | .OrderBy(g => -g.Count())
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| 157 | .Select(g => g.Key)
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| 158 | .First();
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[5816] | 159 | }
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| 160 | }
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| 161 | }
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