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source: branches/GP.Grammar.Editor/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicDiscriminantFunctionClassificationSolution.cs @ 6284

Last change on this file since 6284 was 5975, checked in by mkommend, 14 years ago

#1313: Updated view names to use spaces instead of !camelCasing.

File size: 3.8 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Optimization;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
30  /// <summary>
31  /// Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity
32  /// </summary>
33  [StorableClass]
34  [Item(Name = "SymbolicDiscriminantFunctionClassificationSolution", Description = "Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity.")]
35  public sealed class SymbolicDiscriminantFunctionClassificationSolution : DiscriminantFunctionClassificationSolution, ISymbolicClassificationSolution {
36    private const string ModelLengthResultName = "Model Length";
37    private const string ModelDepthResultName = "Model Depth";
38
39    public new ISymbolicDiscriminantFunctionClassificationModel Model {
40      get { return (ISymbolicDiscriminantFunctionClassificationModel)base.Model; }
41      set { base.Model = value; }
42    }
43
44    ISymbolicClassificationModel ISymbolicClassificationSolution.Model {
45      get { return Model; }
46    }
47
48    ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
49      get { return Model; }
50    }
51    public int ModelLength {
52      get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
53      private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
54    }
55
56    public int ModelDepth {
57      get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
58      private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
59    }
60    [StorableConstructor]
61    private SymbolicDiscriminantFunctionClassificationSolution(bool deserializing) : base(deserializing) { }
62    private SymbolicDiscriminantFunctionClassificationSolution(SymbolicDiscriminantFunctionClassificationSolution original, Cloner cloner)
63      : base(original, cloner) {
64    }
65    public SymbolicDiscriminantFunctionClassificationSolution(ISymbolicDiscriminantFunctionClassificationModel model, IClassificationProblemData problemData)
66      : base(model, problemData) {
67      Add(new Result(ModelLengthResultName, "Length of the symbolic classification model.", new IntValue()));
68      Add(new Result(ModelDepthResultName, "Depth of the symbolic classification model.", new IntValue()));
69      RecalculateResults();
70    }
71
72    public override IDeepCloneable Clone(Cloner cloner) {
73      return new SymbolicDiscriminantFunctionClassificationSolution(this, cloner);
74    }
75
76    protected override void OnModelChanged(EventArgs e) {
77      base.OnModelChanged(e);
78      RecalculateResults();
79    }
80
81    private new void RecalculateResults() {
82      ModelLength = Model.SymbolicExpressionTree.Length;
83      ModelDepth = Model.SymbolicExpressionTree.Depth;
84    }
85  }
86}
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