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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicDiscriminantFunctionClassificationSolution.cs @ 5959

Last change on this file since 5959 was 5818, checked in by gkronber, 14 years ago

#1418 Fixed a problem with scaling of regression and classification solutions (moved scale method out of solution into the model because of leaky abstraction).

File size: 3.9 KB
RevLine 
[5649]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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31using HeuristicLab.Optimization;
32using System;
33
34namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
35  /// <summary>
36  /// Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity
37  /// </summary>
38  [StorableClass]
39  [Item(Name = "SymbolicDiscriminantFunctionClassificationSolution", Description = "Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity.")]
[5717]40  public sealed class SymbolicDiscriminantFunctionClassificationSolution : DiscriminantFunctionClassificationSolution, ISymbolicClassificationSolution {
[5736]41    private const string ModelLengthResultName = "ModelLength";
42    private const string ModelDepthResultName = "ModelDepth";
[5649]43
[5717]44    public new ISymbolicDiscriminantFunctionClassificationModel Model {
45      get { return (ISymbolicDiscriminantFunctionClassificationModel)base.Model; }
46      set { base.Model = value; }
[5649]47    }
48
[5678]49    ISymbolicClassificationModel ISymbolicClassificationSolution.Model {
[5717]50      get { return Model; }
[5678]51    }
52
[5649]53    ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
[5717]54      get { return Model; }
[5649]55    }
[5736]56    public int ModelLength {
57      get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
58      private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
59    }
[5649]60
[5736]61    public int ModelDepth {
62      get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
63      private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
64    }
[5649]65    [StorableConstructor]
[5717]66    private SymbolicDiscriminantFunctionClassificationSolution(bool deserializing) : base(deserializing) { }
67    private SymbolicDiscriminantFunctionClassificationSolution(SymbolicDiscriminantFunctionClassificationSolution original, Cloner cloner)
[5649]68      : base(original, cloner) {
69    }
[5717]70    public SymbolicDiscriminantFunctionClassificationSolution(ISymbolicDiscriminantFunctionClassificationModel model, IClassificationProblemData problemData)
[5649]71      : base(model, problemData) {
[5736]72      Add(new Result(ModelLengthResultName, "Length of the symbolic classification model.", new IntValue()));
73      Add(new Result(ModelDepthResultName, "Depth of the symbolic classification model.", new IntValue()));
74      RecalculateResults();
[5649]75    }
76
77    public override IDeepCloneable Clone(Cloner cloner) {
78      return new SymbolicDiscriminantFunctionClassificationSolution(this, cloner);
[5717]79    }
[5736]80
81    protected override void OnModelChanged(EventArgs e) {
82      base.OnModelChanged(e);
83      RecalculateResults();
84    }
85
86    private new void RecalculateResults() {
87      ModelLength = Model.SymbolicExpressionTree.Length;
88      ModelDepth = Model.SymbolicExpressionTree.Depth;
[5818]89    }   
[5649]90  }
91}
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