| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System.Linq;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Operators;
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| 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 31 | using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic;
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| 32 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 33 | using System.Collections.Generic;
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| 34 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols;
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| 35 | using HeuristicLab.Problems.DataAnalysis;
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| 36 | using HeuristicLab.Analysis;
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| 37 | using HeuristicLab.Problems.DataAnalysis.Evaluators;
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| 38 | using HeuristicLab.Optimization.Operators;
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| 39 | using System;
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| 40 |
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| 41 | namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers {
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| 42 | /// <summary>
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| 43 | /// "An operator for analyzing the quality of symbolic regression solutions symbolic expression tree encoding."
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| 44 | /// </summary>
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| 45 | [Item("SymbolicRegressionModelQualityAnalyzer", "An operator for analyzing the quality of symbolic regression solutions symbolic expression tree encoding.")]
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| 46 | [StorableClass]
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| 47 | public sealed class SymbolicRegressionModelQualityAnalyzer : AlgorithmOperator, ISymbolicRegressionAnalyzer {
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| 48 | private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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| 49 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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| 50 | private const string ProblemDataParameterName = "ProblemData";
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| 51 | private const string ResultsParameterName = "Results";
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| 52 |
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| 53 | private const string TrainingMeanSquaredErrorQualityParameterName = "Mean squared error (training)";
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| 54 | private const string MinTrainingMeanSquaredErrorQualityParameterName = "Min mean squared error (training)";
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| 55 | private const string MaxTrainingMeanSquaredErrorQualityParameterName = "Max mean squared error (training)";
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| 56 | private const string AverageTrainingMeanSquaredErrorQualityParameterName = "Average mean squared error (training)";
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| 57 | private const string BestTrainingMeanSquaredErrorQualityParameterName = "Best mean squared error (training)";
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| 58 |
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| 59 | private const string TrainingAverageRelativeErrorQualityParameterName = "Average relative error (training)";
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| 60 | private const string MinTrainingAverageRelativeErrorQualityParameterName = "Min average relative error (training)";
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| 61 | private const string MaxTrainingAverageRelativeErrorQualityParameterName = "Max average relative error (training)";
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| 62 | private const string AverageTrainingAverageRelativeErrorQualityParameterName = "Average average relative error (training)";
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| 63 | private const string BestTrainingAverageRelativeErrorQualityParameterName = "Best average relative error (training)";
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| 64 |
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| 65 | private const string TrainingRSquaredQualityParameterName = "R² (training)";
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| 66 | private const string MinTrainingRSquaredQualityParameterName = "Min R² (training)";
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| 67 | private const string MaxTrainingRSquaredQualityParameterName = "Max R² (training)";
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| 68 | private const string AverageTrainingRSquaredQualityParameterName = "Average R² (training)";
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| 69 | private const string BestTrainingRSquaredQualityParameterName = "Best R² (training)";
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| 70 |
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| 71 | private const string TestMeanSquaredErrorQualityParameterName = "Mean squared error (test)";
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| 72 | private const string MinTestMeanSquaredErrorQualityParameterName = "Min mean squared error (test)";
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| 73 | private const string MaxTestMeanSquaredErrorQualityParameterName = "Max mean squared error (test)";
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| 74 | private const string AverageTestMeanSquaredErrorQualityParameterName = "Average mean squared error (test)";
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| 75 | private const string BestTestMeanSquaredErrorQualityParameterName = "Best mean squared error (test)";
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| 76 |
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| 77 | private const string TestAverageRelativeErrorQualityParameterName = "Average relative error (test)";
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| 78 | private const string MinTestAverageRelativeErrorQualityParameterName = "Min average relative error (test)";
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| 79 | private const string MaxTestAverageRelativeErrorQualityParameterName = "Max average relative error (test)";
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| 80 | private const string AverageTestAverageRelativeErrorQualityParameterName = "Average average relative error (test)";
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| 81 | private const string BestTestAverageRelativeErrorQualityParameterName = "Best average relative error (test)";
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| 82 |
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| 83 | private const string TestRSquaredQualityParameterName = "R² (test)";
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| 84 | private const string MinTestRSquaredQualityParameterName = "Min R² (test)";
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| 85 | private const string MaxTestRSquaredQualityParameterName = "Max R² (test)";
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| 86 | private const string AverageTestRSquaredQualityParameterName = "Average R² (test)";
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| 87 | private const string BestTestRSquaredQualityParameterName = "Best R² (test)";
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| 88 |
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| 89 | private const string RSquaredValuesParameterName = "R²";
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| 90 | private const string MeanSquaredErrorValuesParameterName = "Mean squared error";
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| 91 | private const string RelativeErrorValuesParameterName = "Average relative error";
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| 92 |
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| 93 | private const string TrainingSamplesStartParameterName = "TrainingSamplesStart";
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| 94 | private const string TrainingSamplesEndParameterName = "TrainingSamplesEnd";
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| 95 | private const string TestSamplesStartParameterName = "TestSamplesStart";
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| 96 | private const string TestSamplesEndParameterName = "TestSamplesEnd";
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| 97 | private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
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| 98 | private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
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| 99 |
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| 100 | #region parameter properties
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| 101 | public ScopeTreeLookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
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| 102 | get { return (ScopeTreeLookupParameter<SymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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| 103 | }
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| 104 | public IValueLookupParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
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| 105 | get { return (IValueLookupParameter<ISymbolicExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
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| 106 | }
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| 107 | public IValueLookupParameter<DataAnalysisProblemData> ProblemDataParameter {
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| 108 | get { return (IValueLookupParameter<DataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
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| 109 | }
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| 110 | public IValueLookupParameter<IntValue> TrainingSamplesStartParameter {
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| 111 | get { return (IValueLookupParameter<IntValue>)Parameters[TrainingSamplesStartParameterName]; }
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| 112 | }
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| 113 | public IValueLookupParameter<IntValue> TrainingSamplesEndParameter {
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| 114 | get { return (IValueLookupParameter<IntValue>)Parameters[TrainingSamplesEndParameterName]; }
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| 115 | }
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| 116 | public IValueLookupParameter<IntValue> TestSamplesStartParameter {
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| 117 | get { return (IValueLookupParameter<IntValue>)Parameters[TestSamplesStartParameterName]; }
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| 118 | }
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| 119 | public IValueLookupParameter<IntValue> TestSamplesEndParameter {
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| 120 | get { return (IValueLookupParameter<IntValue>)Parameters[TestSamplesEndParameterName]; }
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| 121 | }
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| 122 | public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
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| 123 | get { return (IValueLookupParameter<DoubleValue>)Parameters[UpperEstimationLimitParameterName]; }
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| 124 | }
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| 125 | public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter {
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| 126 | get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; }
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| 127 | }
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| 128 | public ILookupParameter<ResultCollection> ResultsParameter {
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| 129 | get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
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| 130 | }
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| 131 | #endregion
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| 132 |
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| 133 | [Storable]
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| 134 | private UniformSubScopesProcessor subScopesProcessor;
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| 135 | [Storable]
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| 136 | private MinAverageMaxValueAnalyzer minAvgMaxTrainingMseAnalyzer;
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| 137 | [Storable]
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| 138 | private MinAverageMaxValueAnalyzer minAvgMaxTestMseAnalyzer;
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| 139 | [Storable]
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| 140 | private MinAverageMaxValueAnalyzer minAvgMaxTrainingRSquaredAnalyzer;
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| 141 | [Storable]
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| 142 | private MinAverageMaxValueAnalyzer minAvgMaxTestRSquaredAnalyzer;
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| 143 | [Storable]
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| 144 | private MinAverageMaxValueAnalyzer minAvgMaxTrainingRelErrorAnalyzer;
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| 145 | [Storable]
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| 146 | private MinAverageMaxValueAnalyzer minAvgMaxTestRelErrorAnalyzer;
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| 147 |
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| 148 | public SymbolicRegressionModelQualityAnalyzer()
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| 149 | : base() {
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| 150 | Parameters.Add(new ScopeTreeLookupParameter<SymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees to analyze."));
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| 151 | Parameters.Add(new ValueLookupParameter<ISymbolicExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
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| 152 | Parameters.Add(new ValueLookupParameter<DataAnalysisProblemData>(ProblemDataParameterName, "The problem data containing the input varaibles for the symbolic regression problem."));
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| 153 | Parameters.Add(new ValueLookupParameter<IntValue>(TrainingSamplesStartParameterName, "The first index of the training data set partition on which the model quality values should be calculated."));
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| 154 | Parameters.Add(new ValueLookupParameter<IntValue>(TrainingSamplesEndParameterName, "The last index of the training data set partition on which the model quality values should be calculated."));
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| 155 | Parameters.Add(new ValueLookupParameter<IntValue>(TestSamplesStartParameterName, "The first index of the test data set partition on which the model quality values should be calculated."));
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| 156 | Parameters.Add(new ValueLookupParameter<IntValue>(TestSamplesEndParameterName, "The last index of the test data set partition on which the model quality values should be calculated."));
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| 157 | Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
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| 158 | Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
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| 159 | Parameters.Add(new ValueLookupParameter<DataTable>(MeanSquaredErrorValuesParameterName, "The data table to collect mean squared error values."));
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| 160 | Parameters.Add(new ValueLookupParameter<DataTable>(RSquaredValuesParameterName, "The data table to collect R² correlation coefficient values."));
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| 161 | Parameters.Add(new ValueLookupParameter<DataTable>(RelativeErrorValuesParameterName, "The data table to collect relative error values."));
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| 162 | Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The result collection where the best symbolic regression solution should be stored."));
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| 163 |
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| 164 | #region operator initialization
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| 165 | subScopesProcessor = new UniformSubScopesProcessor();
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| 166 | SymbolicRegressionModelQualityCalculator trainingQualityCalculator = new SymbolicRegressionModelQualityCalculator();
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| 167 | SymbolicRegressionModelQualityCalculator testQualityCalculator = new SymbolicRegressionModelQualityCalculator();
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| 168 | minAvgMaxTrainingMseAnalyzer = new MinAverageMaxValueAnalyzer();
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| 169 | minAvgMaxTestMseAnalyzer = new MinAverageMaxValueAnalyzer();
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| 170 |
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| 171 | minAvgMaxTrainingRSquaredAnalyzer = new MinAverageMaxValueAnalyzer();
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| 172 | minAvgMaxTestRSquaredAnalyzer = new MinAverageMaxValueAnalyzer();
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| 173 |
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| 174 | minAvgMaxTrainingRelErrorAnalyzer = new MinAverageMaxValueAnalyzer();
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| 175 | minAvgMaxTestRelErrorAnalyzer = new MinAverageMaxValueAnalyzer();
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| 176 | #endregion
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| 177 |
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| 178 | #region parameter wiring
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| 179 | subScopesProcessor.Depth.Value = SymbolicExpressionTreeParameter.Depth;
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| 180 | trainingQualityCalculator.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
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| 181 | trainingQualityCalculator.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
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| 182 | trainingQualityCalculator.SamplesStartParameter.ActualName = TrainingSamplesStartParameter.Name;
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| 183 | trainingQualityCalculator.SamplesEndParameter.ActualName = TrainingSamplesEndParameter.Name;
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| 184 | trainingQualityCalculator.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
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| 185 | trainingQualityCalculator.SymbolicExpressionTreeParameter.ActualName = SymbolicExpressionTreeParameter.Name;
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| 186 | trainingQualityCalculator.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
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| 187 | trainingQualityCalculator.AverageRelativeErrorQualityParameter.ActualName = TrainingAverageRelativeErrorQualityParameterName;
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| 188 | trainingQualityCalculator.MeanSquaredErrorQualityParameter.ActualName = TrainingMeanSquaredErrorQualityParameterName;
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| 189 | trainingQualityCalculator.RSquaredQualityParameter.ActualName = TrainingRSquaredQualityParameterName;
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| 190 |
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| 191 | testQualityCalculator.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
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| 192 | testQualityCalculator.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
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| 193 | testQualityCalculator.SamplesStartParameter.ActualName = TestSamplesStartParameter.Name;
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| 194 | testQualityCalculator.SamplesEndParameter.ActualName = TestSamplesEndParameter.Name;
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| 195 | testQualityCalculator.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
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| 196 | testQualityCalculator.SymbolicExpressionTreeParameter.ActualName = SymbolicExpressionTreeParameter.Name;
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| 197 | testQualityCalculator.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
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| 198 | testQualityCalculator.AverageRelativeErrorQualityParameter.ActualName = TestAverageRelativeErrorQualityParameterName;
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| 199 | testQualityCalculator.MeanSquaredErrorQualityParameter.ActualName = TestMeanSquaredErrorQualityParameterName;
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| 200 | testQualityCalculator.RSquaredQualityParameter.ActualName = TestRSquaredQualityParameterName;
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| 201 | #region training/test MSE
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| 202 | minAvgMaxTrainingMseAnalyzer.ValueParameter.ActualName = TrainingMeanSquaredErrorQualityParameterName;
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| 203 | minAvgMaxTrainingMseAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 204 | minAvgMaxTrainingMseAnalyzer.AverageValueParameter.ActualName = AverageTrainingMeanSquaredErrorQualityParameterName;
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| 205 | minAvgMaxTrainingMseAnalyzer.MaxValueParameter.ActualName = MaxTrainingMeanSquaredErrorQualityParameterName;
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| 206 | minAvgMaxTrainingMseAnalyzer.MinValueParameter.ActualName = MinTrainingMeanSquaredErrorQualityParameterName;
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| 207 | minAvgMaxTrainingMseAnalyzer.ValuesParameter.ActualName = MeanSquaredErrorValuesParameterName;
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| 208 | minAvgMaxTrainingMseAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 209 | minAvgMaxTrainingMseAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 210 | minAvgMaxTrainingMseAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 211 | minAvgMaxTrainingMseAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 212 |
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| 213 | minAvgMaxTestMseAnalyzer.ValueParameter.ActualName = TestMeanSquaredErrorQualityParameterName;
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| 214 | minAvgMaxTestMseAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 215 | minAvgMaxTestMseAnalyzer.AverageValueParameter.ActualName = AverageTestMeanSquaredErrorQualityParameterName;
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| 216 | minAvgMaxTestMseAnalyzer.MaxValueParameter.ActualName = MaxTestMeanSquaredErrorQualityParameterName;
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| 217 | minAvgMaxTestMseAnalyzer.MinValueParameter.ActualName = MinTestMeanSquaredErrorQualityParameterName;
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| 218 | minAvgMaxTestMseAnalyzer.ValuesParameter.ActualName = MeanSquaredErrorValuesParameterName;
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| 219 | minAvgMaxTestMseAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 220 | minAvgMaxTestMseAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 221 | minAvgMaxTestMseAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 222 | minAvgMaxTestMseAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 223 |
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| 224 | #endregion
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| 225 | #region training/test R²
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| 226 | minAvgMaxTrainingRSquaredAnalyzer.ValueParameter.ActualName = TrainingRSquaredQualityParameterName;
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| 227 | minAvgMaxTrainingRSquaredAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 228 | minAvgMaxTrainingRSquaredAnalyzer.AverageValueParameter.ActualName = AverageTrainingRSquaredQualityParameterName;
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| 229 | minAvgMaxTrainingRSquaredAnalyzer.MaxValueParameter.ActualName = MaxTrainingRSquaredQualityParameterName;
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| 230 | minAvgMaxTrainingRSquaredAnalyzer.MinValueParameter.ActualName = MinTrainingRSquaredQualityParameterName;
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| 231 | minAvgMaxTrainingRSquaredAnalyzer.ValuesParameter.ActualName = RSquaredValuesParameterName;
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| 232 | minAvgMaxTrainingRSquaredAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 233 | minAvgMaxTrainingRSquaredAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 234 | minAvgMaxTrainingRSquaredAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 235 | minAvgMaxTrainingRSquaredAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 236 |
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| 237 |
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| 238 | minAvgMaxTestRSquaredAnalyzer.ValueParameter.ActualName = TestRSquaredQualityParameterName;
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| 239 | minAvgMaxTestRSquaredAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 240 | minAvgMaxTestRSquaredAnalyzer.AverageValueParameter.ActualName = AverageTestRSquaredQualityParameterName;
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| 241 | minAvgMaxTestRSquaredAnalyzer.MaxValueParameter.ActualName = MaxTestRSquaredQualityParameterName;
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| 242 | minAvgMaxTestRSquaredAnalyzer.MinValueParameter.ActualName = MinTestRSquaredQualityParameterName;
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| 243 | minAvgMaxTestRSquaredAnalyzer.ValuesParameter.ActualName = RSquaredValuesParameterName;
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| 244 | minAvgMaxTestRSquaredAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 245 | minAvgMaxTestRSquaredAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 246 | minAvgMaxTestRSquaredAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 247 | minAvgMaxTestRSquaredAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 248 |
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| 249 | #endregion
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| 250 | #region training/test avg. rel. error
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| 251 | minAvgMaxTrainingRelErrorAnalyzer.ValueParameter.ActualName = TrainingAverageRelativeErrorQualityParameterName;
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| 252 | minAvgMaxTrainingRelErrorAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 253 | minAvgMaxTrainingRelErrorAnalyzer.AverageValueParameter.ActualName = AverageTrainingAverageRelativeErrorQualityParameterName;
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| 254 | minAvgMaxTrainingRelErrorAnalyzer.MaxValueParameter.ActualName = MaxTrainingAverageRelativeErrorQualityParameterName;
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| 255 | minAvgMaxTrainingRelErrorAnalyzer.MinValueParameter.ActualName = MinTrainingAverageRelativeErrorQualityParameterName;
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| 256 | minAvgMaxTrainingRelErrorAnalyzer.ValuesParameter.ActualName = RelativeErrorValuesParameterName;
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| 257 | minAvgMaxTrainingRelErrorAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 258 | minAvgMaxTrainingRelErrorAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 259 | minAvgMaxTrainingRelErrorAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 260 | minAvgMaxTrainingRelErrorAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 261 |
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| 262 | minAvgMaxTestRelErrorAnalyzer.ValueParameter.ActualName = TestAverageRelativeErrorQualityParameterName;
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| 263 | minAvgMaxTestRelErrorAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 264 | minAvgMaxTestRelErrorAnalyzer.AverageValueParameter.ActualName = AverageTestAverageRelativeErrorQualityParameterName;
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| 265 | minAvgMaxTestRelErrorAnalyzer.MaxValueParameter.ActualName = MaxTestAverageRelativeErrorQualityParameterName;
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| 266 | minAvgMaxTestRelErrorAnalyzer.MinValueParameter.ActualName = MinTestAverageRelativeErrorQualityParameterName;
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| 267 | minAvgMaxTestRelErrorAnalyzer.ValuesParameter.ActualName = RelativeErrorValuesParameterName;
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| 268 | minAvgMaxTestRelErrorAnalyzer.ResultsParameter.ActualName = ResultsParameter.Name;
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| 269 | minAvgMaxTestRelErrorAnalyzer.CollectMinValueInResultsParameter.Value = new BoolValue(false);
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| 270 | minAvgMaxTestRelErrorAnalyzer.CollectAverageValueInResultsParameter.Value = new BoolValue(false);
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| 271 | minAvgMaxTestRelErrorAnalyzer.CollectMaxValueInResultsParameter.Value = new BoolValue(false);
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| 272 | #endregion
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| 273 | #endregion
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| 274 |
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| 275 | #region operator graph
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| 276 | OperatorGraph.InitialOperator = subScopesProcessor;
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| 277 | subScopesProcessor.Operator = trainingQualityCalculator;
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| 278 | trainingQualityCalculator.Successor = testQualityCalculator;
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| 279 | testQualityCalculator.Successor = null;
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| 280 | subScopesProcessor.Successor = minAvgMaxTrainingMseAnalyzer;
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| 281 | minAvgMaxTrainingMseAnalyzer.Successor = minAvgMaxTestMseAnalyzer;
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| 282 | minAvgMaxTestMseAnalyzer.Successor = minAvgMaxTrainingRSquaredAnalyzer;
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| 283 | minAvgMaxTrainingRSquaredAnalyzer.Successor = minAvgMaxTestRSquaredAnalyzer;
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| 284 | minAvgMaxTestRSquaredAnalyzer.Successor = minAvgMaxTrainingRelErrorAnalyzer;
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| 285 | minAvgMaxTrainingRelErrorAnalyzer.Successor = minAvgMaxTestRelErrorAnalyzer;
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| 286 | minAvgMaxTestRelErrorAnalyzer.Successor = null;
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| 287 | #endregion
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| 288 |
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| 289 | Initialize();
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| 290 | }
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| 291 |
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| 292 | [StorableConstructor]
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| 293 | private SymbolicRegressionModelQualityAnalyzer(bool deserializing) : base() { }
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| 294 |
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| 295 | [StorableHook(HookType.AfterDeserialization)]
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| 296 | private void Initialize() {
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| 297 | SymbolicExpressionTreeParameter.DepthChanged += new EventHandler(SymbolicExpressionTreeParameter_DepthChanged);
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| 298 | }
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| 299 |
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| 300 | public override IDeepCloneable Clone(Cloner cloner) {
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| 301 | SymbolicRegressionModelQualityAnalyzer clone = (SymbolicRegressionModelQualityAnalyzer)base.Clone(cloner);
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| 302 | clone.Initialize();
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| 303 | return clone;
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| 304 | }
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| 305 |
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| 306 | private void SymbolicExpressionTreeParameter_DepthChanged(object sender, EventArgs e) {
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| 307 | subScopesProcessor.Depth.Value = SymbolicExpressionTreeParameter.Depth;
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| 308 | minAvgMaxTrainingMseAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 309 | minAvgMaxTrainingRelErrorAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 310 | minAvgMaxTrainingRSquaredAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 311 | minAvgMaxTestMseAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 312 | minAvgMaxTestRelErrorAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 313 | minAvgMaxTestRSquaredAnalyzer.ValueParameter.Depth = SymbolicExpressionTreeParameter.Depth;
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| 314 | }
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| 315 | }
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| 316 | }
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