[18191] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 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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| 24 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 25 |
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| 26 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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| 27 | public static class LinearScaling {
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| 28 |
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| 29 | public static ISymbolicExpressionTree AddLinearScalingTerms(ISymbolicExpressionTree tree, double offset = 0.0, double scale = 1.0) {
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| 30 | var startNode = tree.Root.Subtrees.First();
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| 31 | var template = startNode.Subtrees.First();
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| 32 |
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| 33 | var addNode = new Addition().CreateTreeNode();
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| 34 | var mulNode = new Multiplication().CreateTreeNode();
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| 35 | var offsetNode = new NumberTreeNode(offset);
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| 36 | var scaleNode = new NumberTreeNode(scale);
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| 37 |
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| 38 | addNode.AddSubtree(offsetNode);
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| 39 | addNode.AddSubtree(mulNode);
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| 40 | mulNode.AddSubtree(scaleNode);
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| 41 |
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| 42 | startNode.RemoveSubtree(0);
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| 43 | startNode.AddSubtree(addNode);
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| 44 | mulNode.AddSubtree(template);
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| 45 | return tree;
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| 46 | }
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| 47 |
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| 48 | public static void RemoveLinearScalingTerms(ISymbolicExpressionTree tree) {
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| 49 | var startNode = tree.Root.GetSubtree(0);
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| 50 | ExtractScalingTerms(tree, out NumberTreeNode offsetNode, out NumberTreeNode scaleNode);
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| 51 |
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| 52 | var evaluationNode = scaleNode.Parent.GetSubtree(1); //move up to multiplication and take second child
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| 53 | startNode.RemoveSubtree(0);
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| 54 | startNode.AddSubtree(evaluationNode);
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| 55 | }
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| 56 |
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| 57 | public static void ExtractScalingTerms(ISymbolicExpressionTree tree,
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| 58 | out NumberTreeNode offset, out NumberTreeNode scale) {
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| 59 | var startNode = tree.Root.Subtrees.First();
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| 60 |
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| 61 | //check for scaling terms
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| 62 | var addNode = startNode.GetSubtree(0);
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| 63 | var offsetNode = addNode.GetSubtree(0);
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| 64 | var mulNode = addNode.GetSubtree(1);
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| 65 | var scaleNode = mulNode.GetSubtree(0);
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| 66 |
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| 67 |
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| 68 | var error = false;
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| 69 | if (addNode.Symbol is not Addition) error = true;
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| 70 | if (mulNode.Symbol is not Multiplication) error = true;
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| 71 | if (offsetNode is not NumberTreeNode) error = true;
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| 72 | if (scaleNode is not NumberTreeNode) error = true;
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| 73 | if (error) throw new ArgumentException("Scaling terms cannot be found.");
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| 74 |
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| 75 | offset = (NumberTreeNode)offsetNode;
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| 76 | scale = (NumberTreeNode)scaleNode;
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| 77 | }
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| 78 |
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| 79 | public static void AdjustLinearScalingParams(IRegressionProblemData problemData, ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter) {
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| 80 | ExtractScalingTerms(tree, out NumberTreeNode offsetNode, out NumberTreeNode scaleNode);
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| 81 |
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| 82 | var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, problemData.TrainingIndices);
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| 83 | var targetValues = problemData.TargetVariableTrainingValues;
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| 84 |
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| 85 | OnlineLinearScalingParameterCalculator.Calculate(estimatedValues, targetValues, out double a, out double b, out OnlineCalculatorError error);
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| 86 | if (error == OnlineCalculatorError.None) {
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| 87 | offsetNode.Value = a;
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| 88 | scaleNode.Value = b;
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| 89 | }
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| 90 | }
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| 91 | }
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| 92 | }
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