[2034] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2008 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.Collections.Generic;
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| 24 | using System.Text;
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| 25 | using System.Xml;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.DataAnalysis;
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| 29 | using System.Linq;
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| 30 |
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| 31 | namespace HeuristicLab.Modeling {
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| 32 | public class VariableImpactCalculator : OperatorBase {
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| 33 | public override string Description {
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| 34 | get { return @"Calculates the impact of all allowed input variables on the quality of the model using evaluator supplied as suboperator."; }
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| 35 | }
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| 36 |
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| 37 | public VariableImpactCalculator()
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| 38 | : base() {
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| 39 | AddVariableInfo(new VariableInfo("Dataset", "Dataset", typeof(Dataset), VariableKind.In));
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| 40 | AddVariableInfo(new VariableInfo("TargetVariable", "TargetVariable", typeof(IntData), VariableKind.In));
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| 41 | AddVariableInfo(new VariableInfo("AllowedFeatures", "Indexes of allowed input variables", typeof(ItemList<IntData>), VariableKind.In));
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| 42 | AddVariableInfo(new VariableInfo("TrainingSamplesStart", "TrainingSamplesStart", typeof(IntData), VariableKind.In));
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| 43 | AddVariableInfo(new VariableInfo("TrainingSamplesEnd", "TrainingSamplesEnd", typeof(IntData), VariableKind.In));
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| 44 | AddVariableInfo(new VariableInfo("VariableImpacts", "Variable impacts", typeof(ItemList), VariableKind.New));
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| 45 | }
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| 46 |
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| 47 | public override IOperation Apply(IScope scope) {
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| 48 | ItemList<IntData> allowedFeatures = GetVariableValue<ItemList<IntData>>("AllowedFeatures", scope, true);
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| 49 | int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
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| 50 | Dataset dataset = GetVariableValue<Dataset>("Dataset", scope, true);
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| 51 | Dataset dirtyDataset = (Dataset)dataset.Clone();
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| 52 | int start = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
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| 53 | int end = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
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| 54 |
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| 55 | if (SubOperators.Count < 1) throw new InvalidOperationException("VariableImpactCalculator needs a suboperator to evaluate the model");
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| 56 | IOperator evaluationOperator = this.SubOperators[0];
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| 57 |
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| 58 | ItemList variableImpacts = new ItemList();
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| 59 |
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| 60 | // calculateReferenceQuality
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| 61 | double referenceQuality = CalculateQuality(scope, dataset, evaluationOperator);
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| 62 |
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| 63 | for (int i = 0; i < allowedFeatures.Count; i++) {
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| 64 | int currentVariable = allowedFeatures[i].Data;
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| 65 | var oldValues = ReplaceVariableValues(dirtyDataset, currentVariable , CalculateNewValues(dirtyDataset, currentVariable, start, end), start, end);
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| 66 | double newQuality = CalculateQuality(scope, dirtyDataset, evaluationOperator);
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| 67 | double ratio = referenceQuality / newQuality;
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| 68 | double impact = ratio < 1.0 ? 1.0 - ratio : 1.0 - 1.0 / ratio;
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| 69 | ItemList row = new ItemList();
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| 70 | row.Add(new StringData(dataset.GetVariableName(currentVariable)));
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| 71 | row.Add(new DoubleData(impact));
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| 72 | variableImpacts.Add(row);
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| 73 | ReplaceVariableValues(dirtyDataset, currentVariable, oldValues, start, end);
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| 74 | }
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| 75 | scope.AddVariable(new Variable(scope.TranslateName("VariableImpacts"), variableImpacts));
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| 76 | return null;
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| 77 | }
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| 78 |
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| 79 | private double CalculateQuality(IScope scope, Dataset dataset, IOperator evaluationOperator) {
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| 80 | Scope s = new Scope();
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| 81 | s.AddVariable(new Variable("Dataset", dataset));
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| 82 | scope.AddSubScope(s);
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| 83 | evaluationOperator.Execute(s);
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| 84 | double quality = s.GetVariableValue<DoubleData>("Quality", false).Data;
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| 85 | scope.RemoveSubScope(s);
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| 86 | return quality;
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| 87 | }
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| 88 |
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| 89 | private IEnumerable<double> ReplaceVariableValues(Dataset ds, int variableIndex, IEnumerable<double> newValues, int start, int end) {
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| 90 | double[] oldValues = new double[end - start];
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| 91 | for (int i = 0; i < end - start; i++) oldValues[i] = ds.GetValue(i + start, variableIndex);
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| 92 | if (newValues.Count() != end - start) throw new ArgumentException("The length of the new values sequence doesn't match the required length (number of replaced values)");
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| 93 |
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| 94 | int index = start;
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| 95 | foreach(double v in newValues) {
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| 96 | ds.SetValue(index++, variableIndex, v);
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| 97 | }
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| 98 | return oldValues;
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| 99 | }
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| 100 |
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| 101 | private IEnumerable<double> CalculateNewValues(Dataset ds, int variableIndex, int start, int end) {
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| 102 | double mean = ds.GetMean(variableIndex, start, end);
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| 103 | return Enumerable.Repeat(mean, end - start);
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| 104 | }
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| 105 | }
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| 106 | }
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