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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionMeanSquaredErrorEvaluator.cs @ 3374

Last change on this file since 3374 was 3374, checked in by gkronber, 12 years ago

Refactored HeuristicLab.Problems.DataAnalysis namespace. #938 (Data types and operators for regression problems)

File size: 2.8 KB
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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;
23using System.Collections.Generic;
24using System.Linq;
25using System.Drawing;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.PluginInfrastructure;
33using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
34using HeuristicLab.Problems.DataAnalysis;
35using HeuristicLab.Operators;
36using HeuristicLab.Problems.DataAnalysis.Evaluators;
37using HeuristicLab.Problems.DataAnalysis.Symbolic;
38
39namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
40  [Item("SymbolicRegressionMeanSquaredErrorEvaluator", "Calculates the mean squared error of a symbolic regression solution.")]
41  [StorableClass]
42  public class SymbolicRegressionMeanSquaredErrorEvaluator : SymbolicRegressionEvaluator {
43    protected override double Evaluate(SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IntValue samplesStart, IntValue samplesEnd, DoubleValue numberOfEvaluatedNodes) {
44      double mse = Calculate(solution, dataset, targetVariable.Value, samplesStart.Value, samplesEnd.Value);
45      numberOfEvaluatedNodes.Value += solution.Size * (samplesEnd.Value - samplesStart.Value);
46      return mse;
47    }
48
49    public static double Calculate(SymbolicExpressionTree solution, Dataset dataset, string targetVariable, int start, int end) {
50      SimpleArithmeticExpressionEvaluator evaluator = new SimpleArithmeticExpressionEvaluator();
51      int targetVariableIndex = dataset.GetVariableIndex(targetVariable);
52      var estimatedValues = evaluator.EstimatedValues(solution, dataset, Enumerable.Range(start, end - start));
53      var originalValues = from row in Enumerable.Range(start, end - start) select dataset[row, targetVariableIndex];
54      return SimpleMSEEvaluator.Calculate(originalValues, estimatedValues);
55    }
56  }
57}
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