source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs @ 14185

Last change on this file since 14185 was 14185, checked in by swagner, 5 years ago

#2526: Updated year of copyrights in license headers

File size: 2.9 KB
Line 
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.Encodings.SymbolicExpressionTreeEncoding;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
29  /// <summary>
30  /// Represents a symbolic classification model
31  /// </summary>
32  [StorableClass]
33  [Item(Name = "SymbolicClassificationModel", Description = "Represents a symbolic classification model.")]
34  public abstract class SymbolicClassificationModel : SymbolicDataAnalysisModel, ISymbolicClassificationModel {
35    [Storable]
36    private readonly string targetVariable;
37    public string TargetVariable {
38      get { return targetVariable; }
39    }
40
41    [StorableConstructor]
42    protected SymbolicClassificationModel(bool deserializing) : base(deserializing) { }
43
44    protected SymbolicClassificationModel(SymbolicClassificationModel original, Cloner cloner)
45      : base(original, cloner) {
46      targetVariable = original.targetVariable;
47    }
48
49    protected SymbolicClassificationModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
50      : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) {
51      this.targetVariable = targetVariable;
52    }
53
54    public abstract IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows);
55    public abstract void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
56
57    public abstract ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
58
59    IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
60      return CreateClassificationSolution(problemData);
61    }
62
63    public void Scale(IClassificationProblemData problemData) {
64      Scale(problemData, problemData.TargetVariable);
65    }
66  }
67}
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