source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionModel.cs @ 4468

Last change on this file since 4468 was 4468, checked in by mkommend, 9 years ago

Preparation for cross validation - removed the test samples from the trainining samples and added ValidationPercentage parameter (ticket #1199).

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis.Symbolic;
29using HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols;
30
31namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
32  [StorableClass]
33  [Item("SymbolicRegressionModel", "A symbolic regression model represents an entity that provides estimated values based on input values.")]
34  public class SymbolicRegressionModel : NamedItem, IDataAnalysisModel {
35    private SymbolicRegressionModel() : base() { } // for cloning
36    [StorableConstructor]
37    protected SymbolicRegressionModel(bool deserializing)
38      : base(deserializing) {
39    }
40    public SymbolicRegressionModel(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree tree)
41      : base() {
42      this.tree = tree;
43      this.interpreter = interpreter;
44      this.inputVariables = tree.IterateNodesPrefix().OfType<VariableTreeNode>().Select(var => var.VariableName).Distinct().ToList();
45    }
46
47    [StorableHook(HookType.AfterDeserialization)]
48    private void AfterDeserializationHook() {
49      if (inputVariables == null)
50        this.inputVariables = tree.IterateNodesPrefix().OfType<VariableTreeNode>().Select(var => var.VariableName).Distinct().ToList();
51    }
52
53    [Storable]
54    private SymbolicExpressionTree tree;
55    public SymbolicExpressionTree SymbolicExpressionTree {
56      get { return tree; }
57    }
58    [Storable]
59    private ISymbolicExpressionTreeInterpreter interpreter;
60    public ISymbolicExpressionTreeInterpreter Interpreter {
61      get { return interpreter; }
62    }
63    [Storable]
64    private List<string> inputVariables;
65    public IEnumerable<string> InputVariables {
66      get { return inputVariables.AsEnumerable(); }
67    }
68
69    public IEnumerable<double> GetEstimatedValues(DataAnalysisProblemData problemData, int start, int end) {
70      return GetEstimatedValues(problemData, Enumerable.Range(start, end - start));
71    }
72    public IEnumerable<double> GetEstimatedValues(DataAnalysisProblemData problemData, IEnumerable<int> rows) {
73      return interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, rows);
74    }
75
76    public override IDeepCloneable Clone(Cloner cloner) {
77      var clone = (SymbolicRegressionModel)base.Clone(cloner);
78      clone.tree = (SymbolicExpressionTree)cloner.Clone(tree);
79      clone.interpreter = (ISymbolicExpressionTreeInterpreter)cloner.Clone(interpreter);
80      clone.inputVariables = new List<string>(inputVariables);
81      return clone;
82    }
83  }
84}
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