[10596] | 1 | #region License Information
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| 2 |
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| 3 | /* HeuristicLab
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| 4 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 5 | *
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| 6 | * This file is part of HeuristicLab.
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| 7 | *
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| 8 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 9 | * it under the terms of the GNU General Public License as published by
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| 10 | * the Free Software Foundation, either version 3 of the License, or
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| 11 | * (at your option) any later version.
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| 12 | *
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| 13 | * HeuristicLab is distributed in the hope that it will be useful,
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| 14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 16 | * GNU General Public License for more details.
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| 17 | *
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| 18 | * You should have received a copy of the GNU General Public License
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| 19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 20 | */
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| 21 |
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| 22 | #endregion
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| 23 |
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| 24 | using System;
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| 25 | using System.Linq;
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| 26 | using HeuristicLab.Analysis;
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| 27 | using HeuristicLab.Common;
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| 28 | using HeuristicLab.Core;
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| 29 | using HeuristicLab.Operators;
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| 30 | using HeuristicLab.Optimization;
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| 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 33 |
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| 34 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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| 35 | public class SymbolicRegressionSolutionsAnalyzer : SingleSuccessorOperator, IAnalyzer {
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| 36 | private const string ResultCollectionParameterName = "Results";
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| 37 | private const string RegressionSolutionQualitiesResultName = "Regression Solution Qualities";
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| 38 |
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| 39 | public ILookupParameter<ResultCollection> ResultCollectionParameter {
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| 40 | get { return (ILookupParameter<ResultCollection>)Parameters[ResultCollectionParameterName]; }
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| 41 | }
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| 42 |
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| 43 | public virtual bool EnabledByDefault {
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| 44 | get { return false; }
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| 45 | }
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| 46 |
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| 47 | [StorableConstructor]
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| 48 | protected SymbolicRegressionSolutionsAnalyzer(bool deserializing) : base(deserializing) { }
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| 49 | protected SymbolicRegressionSolutionsAnalyzer(SymbolicRegressionSolutionsAnalyzer original, Cloner cloner)
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| 50 | : base(original, cloner) { }
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| 51 | public override IDeepCloneable Clone(Cloner cloner) {
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| 52 | return new SymbolicRegressionSolutionsAnalyzer(this, cloner);
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| 53 | }
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| 54 |
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| 55 | public SymbolicRegressionSolutionsAnalyzer() {
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| 56 | Parameters.Add(new LookupParameter<ResultCollection>(ResultCollectionParameterName, "The result collection to store the analysis results."));
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| 57 | }
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| 58 |
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| 59 | public override IOperation Apply() {
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| 60 | var results = ResultCollectionParameter.ActualValue;
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| 61 |
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| 62 | if (!results.ContainsKey(RegressionSolutionQualitiesResultName)) {
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| 63 | var newDataTable = new DataTable(RegressionSolutionQualitiesResultName);
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| 64 | results.Add(new Result(RegressionSolutionQualitiesResultName, "Chart displaying the training and test qualities of the regression solutions.", newDataTable));
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| 65 | }
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| 66 |
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| 67 | var dataTable = (DataTable)results[RegressionSolutionQualitiesResultName].Value;
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| 68 | foreach (var result in results.Where(r => r.Value is IRegressionSolution)) {
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| 69 | var solution = (IRegressionSolution)result.Value;
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| 70 |
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| 71 | var trainingR2 = result.Name + Environment.NewLine + "Training R²";
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| 72 | if (!dataTable.Rows.ContainsKey(trainingR2))
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| 73 | dataTable.Rows.Add(new DataRow(trainingR2));
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| 74 |
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| 75 | var testR2 = result.Name + Environment.NewLine + " Test R²";
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| 76 | if (!dataTable.Rows.ContainsKey(testR2))
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| 77 | dataTable.Rows.Add(new DataRow(testR2));
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| 78 |
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| 79 | dataTable.Rows[trainingR2].Values.Add(solution.TrainingRSquared);
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| 80 | dataTable.Rows[testR2].Values.Add(solution.TestRSquared);
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| 81 | }
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| 82 |
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| 83 | return base.Apply();
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| 84 | }
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| 85 | }
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| 86 | }
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