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.Collections.Generic;
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23 | using System.Linq;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using HeuristicLab.Parameters;
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28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 | using HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Interfaces;
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30 | using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic;
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31 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators {
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34 | [Item("SymbolicVectorRegressionNormalizedMseEvaluator", "Represents an operator that calculates the sum of the normalized mean squared error over all components.")]
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35 | [StorableClass]
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36 | public class SymbolicVectorRegressionNormalizedMseEvaluator : SingleObjectiveSymbolicVectorRegressionEvaluator {
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37 |
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38 |
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39 | public SymbolicVectorRegressionNormalizedMseEvaluator(bool deserializing) : base(deserializing) { }
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40 | public SymbolicVectorRegressionNormalizedMseEvaluator()
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41 | : base() {
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42 | }
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43 |
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44 | public override double Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) {
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45 | return Calculate(tree, interpreter, problemData, targetVariables, rows, lowerEstimationBound, upperEstimationBound);
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46 | }
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47 |
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48 | public static double Calculate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) {
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49 | List<string> targetVariablesList = targetVariables.ToList();
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50 | double nmseSum = 0.0;
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51 | // use only the i-th vector component
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52 | List<SymbolicExpressionTreeNode> componentBranches = new List<SymbolicExpressionTreeNode>(tree.Root.SubTrees[0].SubTrees);
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53 | while (tree.Root.SubTrees[0].SubTrees.Count > 0) tree.Root.SubTrees[0].RemoveSubTree(0);
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54 |
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55 | for (int i = 0; i < targetVariablesList.Count; i++) {
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56 | tree.Root.SubTrees[0].AddSubTree(componentBranches[i]);
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57 | double nmse = SymbolicRegressionNormalizedMeanSquaredErrorEvaluator.Calculate(interpreter, tree,
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58 | lowerEstimationBound[i], upperEstimationBound[i],
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59 | problemData.Dataset, targetVariablesList[i], rows);
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60 | tree.Root.SubTrees[0].RemoveSubTree(0);
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61 | nmseSum += nmse;
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62 | }
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63 | // restore tree
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64 | foreach (var treeNode in componentBranches) {
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65 | tree.Root.SubTrees[0].AddSubTree(treeNode);
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66 | }
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67 | return nmseSum;
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68 | }
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69 | }
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70 | }
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