[3915] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3915] | 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.Linq;
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[6256] | 25 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[5699] | 26 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Views;
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[3915] | 27 |
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[5699] | 28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views {
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| 29 | public partial class InteractiveSymbolicRegressionSolutionSimplifierView : InteractiveSymbolicDataAnalysisSolutionSimplifierView {
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[8946] | 30 | private readonly SymbolicRegressionSolutionImpactValuesCalculator calculator;
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[5717] | 31 |
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| 32 | public new SymbolicRegressionSolution Content {
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| 33 | get { return (SymbolicRegressionSolution)base.Content; }
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| 34 | set { base.Content = value; }
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| 35 | }
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| 36 |
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[5699] | 37 | public InteractiveSymbolicRegressionSolutionSimplifierView()
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| 38 | : base() {
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| 39 | InitializeComponent();
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| 40 | this.Caption = "Interactive Regression Solution Simplifier";
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[8946] | 41 | calculator = new SymbolicRegressionSolutionImpactValuesCalculator();
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[3915] | 42 | }
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| 43 |
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[5717] | 44 | protected override void UpdateModel(ISymbolicExpressionTree tree) {
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[8639] | 45 | var model = new SymbolicRegressionModel(tree, Content.Model.Interpreter, Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit);
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[8972] | 46 | model.Scale(Content.ProblemData);
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[5818] | 47 | Content.Model = model;
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[3915] | 48 | }
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| 49 |
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[5717] | 50 | protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateReplacementValues(ISymbolicExpressionTree tree) {
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[8946] | 51 | return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary(
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| 52 | n => n,
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| 53 | n => calculator.CalculateReplacementValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices)
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| 54 | );
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[3915] | 55 | }
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| 56 |
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[5717] | 57 | protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateImpactValues(ISymbolicExpressionTree tree) {
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[10492] | 58 | var values = CalculateImpactAndReplacementValues(tree);
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| 59 | return values.ToDictionary(x => x.Key, x => x.Value.Item1);
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[3915] | 60 | }
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| 61 |
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[10492] | 62 | protected override Dictionary<ISymbolicExpressionTreeNode, Tuple<double, double>> CalculateImpactAndReplacementValues(ISymbolicExpressionTree tree) {
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| 63 | var impactAndReplacementValues = new Dictionary<ISymbolicExpressionTreeNode, Tuple<double, double>>();
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| 64 | foreach (var node in tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix()) {
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[12720] | 65 | double impactValue, replacementValue, newQualityForImpactsCalculation;
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| 66 | calculator.CalculateImpactAndReplacementValues(Content.Model, node, Content.ProblemData, Content.ProblemData.TrainingIndices, out impactValue, out replacementValue, out newQualityForImpactsCalculation);
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[10492] | 67 | impactAndReplacementValues.Add(node, new Tuple<double, double>(impactValue, replacementValue));
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| 68 | }
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| 69 | return impactAndReplacementValues;
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| 70 | }
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| 71 |
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[6256] | 72 | protected override void btnOptimizeConstants_Click(object sender, EventArgs e) {
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[8664] | 73 | var model = Content.Model;
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[8946] | 74 | SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(model.Interpreter, model.SymbolicExpressionTree, Content.ProblemData, Content.ProblemData.TrainingIndices,
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[8704] | 75 | applyLinearScaling: true, maxIterations: 50, upperEstimationLimit: model.UpperEstimationLimit, lowerEstimationLimit: model.LowerEstimationLimit);
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[6256] | 76 | UpdateModel(Content.Model.SymbolicExpressionTree);
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| 77 | }
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[3915] | 78 | }
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| 79 | }
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