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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationModel.cs @ 13941

Last change on this file since 13941 was 13941, checked in by mkommend, 8 years ago

#2604:

  • Base classes for data analysis, classification, and regression models
  • Added target variable to classification and regression models
  • Switched parameter order in data analysis solutions (model, problemdata)
File size: 2.3 KB
RevLine 
[13941]1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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.Core;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  [StorableClass]
29  [Item("Classification Model", "Base class for all classification models.")]
30  public abstract class ClassificationModel : DataAnalysisModel, IClassificationModel {
31    [Storable]
32    private string targetVariable;
33    public string TargetVariable {
34      get { return targetVariable; }
35      protected set { targetVariable = value; }
36    }
37
38    protected ClassificationModel(bool deserializing) : base(deserializing) { }
39    protected ClassificationModel(ClassificationModel original, Cloner cloner)
40      : base(original, cloner) {
41      this.targetVariable = original.targetVariable;
42    }
43
44    protected ClassificationModel(string targetVariable)
45      : base("Classification Model") {
46      this.targetVariable = targetVariable;
47    }
48    protected ClassificationModel(string targetVariable, string name)
49      : base(name) {
50      this.targetVariable = targetVariable;
51    }
52    protected ClassificationModel(string targetVariable, string name, string description)
53      : base(name, description) {
54      this.targetVariable = targetVariable;
55    }
56
57    public abstract IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows);
58    public abstract IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
59  }
60}
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