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source: branches/OaaS/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs @ 11328

Last change on this file since 11328 was 9363, checked in by spimming, 12 years ago

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[5624]1#region License Information
2/* HeuristicLab
[7259]3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5624]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.")]
[9363]34  public abstract class
35    SymbolicClassificationModel : SymbolicDataAnalysisModel, ISymbolicClassificationModel {
36    [Storable]
37    private double lowerEstimationLimit;
38    public double LowerEstimationLimit { get { return lowerEstimationLimit; } }
39    [Storable]
40    private double upperEstimationLimit;
41    public double UpperEstimationLimit { get { return upperEstimationLimit; } }
42
[5624]43    [StorableConstructor]
44    protected SymbolicClassificationModel(bool deserializing) : base(deserializing) { }
45    protected SymbolicClassificationModel(SymbolicClassificationModel original, Cloner cloner)
46      : base(original, cloner) {
[9363]47      lowerEstimationLimit = original.lowerEstimationLimit;
48      upperEstimationLimit = original.upperEstimationLimit;
[5624]49    }
[9363]50    protected SymbolicClassificationModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
[5624]51      : base(tree, interpreter) {
[9363]52      this.lowerEstimationLimit = lowerEstimationLimit;
53      this.upperEstimationLimit = upperEstimationLimit;
[5624]54    }
55
[9363]56    public abstract IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows);
57    public abstract void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
[5624]58
[9363]59    public abstract ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
[6604]60
61    IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
62      return CreateClassificationSolution(problemData);
63    }
64
[9363]65    public void Scale(IClassificationProblemData problemData) {
66      Scale(problemData, problemData.TargetVariable);
67    }
[5624]68  }
69}
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