source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionModel.cs @ 14289

Last change on this file since 14289 was 14289, checked in by mkommend, 5 years ago

#2669: Removed the after deserialization method that resets the targetVariable. Instead the initialization code has been added to the storable ctor.

File size: 3.1 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.Regression {
29  /// <summary>
30  /// Represents a symbolic regression model
31  /// </summary>
32  [StorableClass]
33  [Item(Name = "Symbolic Regression Model", Description = "Represents a symbolic regression model.")]
34  public class SymbolicRegressionModel : SymbolicDataAnalysisModel, ISymbolicRegressionModel {
35    [Storable]
36    private readonly string targetVariable;
37    public string TargetVariable {
38      get { return targetVariable; }
39    }
40
41    [StorableConstructor]
42    protected SymbolicRegressionModel(bool deserializing)
43      : base(deserializing) {
44      targetVariable = string.Empty;
45    }
46
47    protected SymbolicRegressionModel(SymbolicRegressionModel original, Cloner cloner)
48      : base(original, cloner) {
49      this.targetVariable = original.targetVariable;
50    }
51
52    public SymbolicRegressionModel(string targetVariable, ISymbolicExpressionTree tree,
53      ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
54      double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
55      : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) {
56      this.targetVariable = targetVariable;
57    }
58
59    public override IDeepCloneable Clone(Cloner cloner) {
60      return new SymbolicRegressionModel(this, cloner);
61    }
62
63    public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
64      return Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows)
65        .LimitToRange(LowerEstimationLimit, UpperEstimationLimit);
66    }
67
68    public ISymbolicRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
69      return new SymbolicRegressionSolution(this, new RegressionProblemData(problemData));
70    }
71    IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
72      return CreateRegressionSolution(problemData);
73    }
74
75    public void Scale(IRegressionProblemData problemData) {
76      Scale(problemData, problemData.TargetVariable);
77    }
78  }
79}
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