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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs @ 12509

Last change on this file since 12509 was 12509, checked in by mkommend, 9 years ago

#2276: Reintegrated branch for dataset refactoring.

File size: 2.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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
36    [StorableConstructor]
37    protected SymbolicClassificationModel(bool deserializing) : base(deserializing) { }
38    protected SymbolicClassificationModel(SymbolicClassificationModel original, Cloner cloner) : base(original, cloner) { }
39    protected SymbolicClassificationModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
40      double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
41      : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) { }
42
43    public abstract IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows);
44    public abstract void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
45
46    public abstract ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
47
48    IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
49      return CreateClassificationSolution(problemData);
50    }
51
52    public void Scale(IClassificationProblemData problemData) {
53      Scale(problemData, problemData.TargetVariable);
54    }
55  }
56}
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