[3378] | 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;
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| 23 | using System.Linq;
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[4044] | 24 | using alglib;
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[3378] | 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Operators;
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[4044] | 28 | using HeuristicLab.Optimization;
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[3378] | 29 | using HeuristicLab.Parameters;
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| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 |
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[4044] | 32 | namespace HeuristicLab.Problems.DataAnalysis.Operators {
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| 33 | [Item("WeightedParentsQualityVarianceComparator", "Compares the quality and variance of the quality against that of its parents (assumes the parents are subscopes to the child scope). This operator works with any number of subscopes > 0.")]
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[3378] | 34 | [StorableClass]
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[4044] | 35 | public class WeightedParentsQualityVarianceComparator : SingleSuccessorOperator, ISubScopesQualityComparator {
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[3378] | 36 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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| 37 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 38 | }
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[4044] | 39 | public ILookupParameter<BoolValue> ResultParameter {
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| 40 | get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
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| 41 | }
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| 42 | public IValueLookupParameter<DoubleValue> ConfidenceIntervalParameter {
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| 43 | get { return (IValueLookupParameter<DoubleValue>)Parameters["ConfidenceInterval"]; }
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| 44 | }
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[3378] | 45 | public ILookupParameter<DoubleValue> LeftSideParameter {
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| 46 | get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
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| 47 | }
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[4044] | 48 | public ILookupParameter<DoubleValue> LeftSideVarianceParameter {
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| 49 | get { return (ILookupParameter<DoubleValue>)Parameters["LeftSideVariance"]; }
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| 50 | }
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| 51 | public ILookupParameter<IntValue> LeftSideSamplesParameter {
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| 52 | get { return (ILookupParameter<IntValue>)Parameters["LeftSideSamples"]; }
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| 53 | }
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[3378] | 54 | public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
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| 55 | get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
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| 56 | }
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[4044] | 57 | public ILookupParameter<ItemArray<DoubleValue>> RightSideVariancesParameters {
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| 58 | get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSideVariances"]; }
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[3378] | 59 | }
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[4044] | 60 | public ILookupParameter<ItemArray<IntValue>> RightSideSamplesParameters {
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| 61 | get { return (ILookupParameter<ItemArray<IntValue>>)Parameters["RightSideSamples"]; }
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[3378] | 62 | }
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| 63 |
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[4044] | 64 | public WeightedParentsQualityVarianceComparator()
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[3378] | 65 | : base() {
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| 66 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
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[4044] | 67 | Parameters.Add(new LookupParameter<BoolValue>("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
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| 68 | Parameters.Add(new ValueLookupParameter<DoubleValue>("ConfidenceInterval", "The confidence interval used for the test.", new DoubleValue(0.05)));
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| 69 |
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[3378] | 70 | Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
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[4044] | 71 | Parameters.Add(new LookupParameter<DoubleValue>("LeftSideVariance", "The variances of the quality of the new child."));
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| 72 | Parameters.Add(new LookupParameter<IntValue>("LeftSideSamples", "The number of samples used to calculate the quality of the new child."));
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| 73 |
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[3659] | 74 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
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[4044] | 75 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSideVariances", "The variances of the parents."));
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[4131] | 76 | Parameters.Add(new ScopeTreeLookupParameter<IntValue>("RightSideSamples", "The number of samples used to calculate the quality of the parent."));
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[3378] | 77 | }
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| 78 |
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| 79 | public override IOperation Apply() {
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[4044] | 80 | double leftQuality = LeftSideParameter.ActualValue.Value;
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| 81 | double leftVariance = LeftSideVarianceParameter.ActualValue.Value;
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| 82 | int leftSamples = LeftSideSamplesParameter.ActualValue.Value;
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| 83 |
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[3378] | 84 | ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
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[4044] | 85 | ItemArray<DoubleValue> rightVariances = RightSideVariancesParameters.ActualValue;
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| 86 | ItemArray<IntValue> rightSamples = RightSideSamplesParameters.ActualValue;
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| 87 |
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[3378] | 88 | if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
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| 89 | bool maximization = MaximizationParameter.ActualValue.Value;
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| 90 |
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[4044] | 91 | int bestParentIndex;
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| 92 | double bestParentQuality;
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| 93 | double bestParentVariance;
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| 94 | int bestParentSamples;
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[3378] | 95 |
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[4044] | 96 | if (maximization)
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| 97 | bestParentQuality = rightQualities.Max(x => x.Value);
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| 98 | else
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| 99 | bestParentQuality = rightQualities.Min(x => x.Value);
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| 100 | bestParentIndex = rightQualities.FindIndex(x => x.Value == bestParentQuality);
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| 101 | bestParentVariance = rightVariances[bestParentIndex].Value;
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| 102 | bestParentSamples = rightSamples[bestParentIndex].Value;
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[3378] | 103 |
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[4044] | 104 | double xmean = leftQuality;
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| 105 | double xvar = leftVariance;
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| 106 | int n = leftSamples;
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| 107 | double ymean = bestParentQuality;
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| 108 | double yvar = bestParentVariance;
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| 109 | double m = bestParentSamples;
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[3378] | 110 |
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[4044] | 111 |
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| 112 | //following code taken from ALGLIB studentttest line 351
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| 113 | // Two-sample unpooled test
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| 114 | double p = 0;
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| 115 | double stat = (xmean - ymean) / Math.Sqrt(xvar / n + yvar / m);
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| 116 | double c = xvar / n / (xvar / n + yvar / m);
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| 117 | double df = (n - 1) * (m - 1) / ((m - 1) * AP.Math.Sqr(c) + (n - 1) * (1 - AP.Math.Sqr(c)));
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| 118 | if ((double)(stat) > (double)(0))
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| 119 | p = 1 - 0.5 * ibetaf.incompletebeta(df / 2, 0.5, df / (df + AP.Math.Sqr(stat)));
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| 120 | else
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| 121 | p = 0.5 * ibetaf.incompletebeta(df / 2, 0.5, df / (df + AP.Math.Sqr(stat)));
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| 122 | double bothtails = 2 * Math.Min(p, 1 - p);
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| 123 | double lefttail = p;
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| 124 | double righttail = 1 - p;
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| 125 |
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| 126 | bool result = false;
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[4193] | 127 | // reject only if the child is significantly worse
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| 128 | if (maximization) {
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| 129 | if (bothtails > ConfidenceIntervalParameter.ActualValue.Value) result = true;
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| 130 | else if (leftQuality > bestParentQuality) result = true;
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| 131 | else result = false;
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| 132 | } else {
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| 133 | if (bothtails > ConfidenceIntervalParameter.ActualValue.Value) result = true;
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| 134 | else if (leftQuality < bestParentQuality) result = true;
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| 135 | else result = false;
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| 136 | }
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[4044] | 137 |
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[3378] | 138 | BoolValue resultValue = ResultParameter.ActualValue;
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| 139 | if (resultValue == null) {
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| 140 | ResultParameter.ActualValue = new BoolValue(result);
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| 141 | } else {
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| 142 | resultValue.Value = result;
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| 143 | }
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| 144 | return base.Apply();
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| 145 | }
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| 146 | }
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| 147 | }
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