Free cookie consent management tool by TermsFeed Policy Generator

source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs @ 5770

Last change on this file since 5770 was 5770, checked in by mkommend, 13 years ago

#1418: Changed data type of estimation limits and corrected some bugs.

File size: 3.9 KB
Line 
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 HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
30  [Item("Mean squared error Evaluator", "Calculates the mean squared error of a symbolic regression solution.")]
31  [StorableClass]
32  public class SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator : SymbolicRegressionSingleObjectiveEvaluator {
33    [StorableConstructor]
34    protected SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator(bool deserializing) : base(deserializing) { }
35    protected SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator(SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator original, Cloner cloner)
36      : base(original, cloner) {
37    }
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator(this, cloner);
40    }
41
42    public SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator() : base() { }
43
44    public override bool Maximization { get { return false; } }
45
46    public override IOperation Apply() {
47      IEnumerable<int> rows = GenerateRowsToEvaluate();
48      double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows);
49      Quality = new DoubleValue(quality);
50      return base.Apply();
51    }
52
53    public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
54      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
55      IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
56      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
57      return OnlineMeanSquaredErrorEvaluator.Calculate(originalValues, boundedEstimationValues);
58    }
59
60    public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IRegressionProblemData problemData, IEnumerable<int> rows) {
61      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
62      EstimationLimitsParameter.ExecutionContext = context;
63
64      double mse = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows);
65
66      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
67      EstimationLimitsParameter.ExecutionContext = null;
68
69      return mse;
70    }
71  }
72}
Note: See TracBrowser for help on using the repository browser.