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source: branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/MetaModels/ComponentReducedLinearModel.cs @ 15430

Last change on this file since 15430 was 15430, checked in by bwerth, 5 years ago

#2847 first implementation of M5'-regression

File size: 2.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.Collections.Generic;
23using HeuristicLab.Common;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25using HeuristicLab.Problems.DataAnalysis;
26
27namespace HeuristicLab.Algorithms.DataAnalysis {
28  [StorableClass]
29  internal class ComponentReducedLinearModel : RegressionModel, IConfidenceRegressionModel {
30    [Storable]
31    private IConfidenceRegressionModel Model;
32    [Storable]
33    private PrincipleComponentAnalysisStatic Pca;
34
35    [StorableConstructor]
36    private ComponentReducedLinearModel(bool deserializing) : base(deserializing) { }
37    private ComponentReducedLinearModel(ComponentReducedLinearModel original, Cloner cloner) : base(original, cloner) {
38      Model = cloner.Clone(original.Model);
39      Pca = cloner.Clone(original.Pca);
40    }
41    public ComponentReducedLinearModel(string targetVariable, IConfidenceRegressionModel model, PrincipleComponentAnalysisStatic pca) : base(targetVariable) {
42      Model = model;
43      Pca = pca;
44    }
45    public override IDeepCloneable Clone(Cloner cloner) {
46      return new ComponentReducedLinearModel(this, cloner);
47    }
48
49    public override IEnumerable<string> VariablesUsedForPrediction {
50      get { return Model.VariablesUsedForPrediction; }
51    }
52    public override IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
53      return Model.GetEstimatedValues(Pca.ProjectDataset(dataset), rows);
54    }
55    public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
56      return new ConfidenceRegressionSolution(this, problemData);
57    }
58    public IEnumerable<double> GetEstimatedVariances(IDataset dataset, IEnumerable<int> rows) {
59      return Model.GetEstimatedVariances(Pca.ProjectDataset(dataset), rows);
60    }
61  }
62}
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