[6642] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11205] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6642] | 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 System.Windows.Forms;
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| 25 | using HeuristicLab.Algorithms.DataAnalysis;
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| 26 | using HeuristicLab.MainForm;
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| 27 | using HeuristicLab.Problems.DataAnalysis.Views;
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| 28 |
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| 29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views {
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| 30 | [View("Error Characteristics Curve")]
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| 31 | [Content(typeof(ISymbolicRegressionSolution))]
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| 32 | public partial class SymbolicRegressionSolutionErrorCharacteristicsCurveView : RegressionSolutionErrorCharacteristicsCurveView {
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| 33 | private IRegressionSolution linearRegressionSolution;
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| 34 | public SymbolicRegressionSolutionErrorCharacteristicsCurveView() {
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| 35 | InitializeComponent();
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| 36 | }
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| 37 |
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| 38 | public new ISymbolicRegressionSolution Content {
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| 39 | get { return (ISymbolicRegressionSolution)base.Content; }
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| 40 | set { base.Content = value; }
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| 41 | }
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| 42 |
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| 43 | protected override void OnContentChanged() {
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| 44 | if (Content != null)
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| 45 | linearRegressionSolution = CreateLinearRegressionSolution();
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| 46 | else
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| 47 | linearRegressionSolution = null;
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| 48 |
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| 49 | base.OnContentChanged();
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| 50 | }
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| 51 |
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| 52 | protected override void UpdateChart() {
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| 53 | base.UpdateChart();
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| 54 | if (Content == null || linearRegressionSolution == null) return;
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| 55 | AddRegressionSolution(linearRegressionSolution);
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| 56 | }
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| 57 |
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| 58 | private IRegressionSolution CreateLinearRegressionSolution() {
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| 59 | if (Content == null) throw new InvalidOperationException();
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| 60 | double rmse, cvRmsError;
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| 61 | var problemData = (IRegressionProblemData)ProblemData.Clone();
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[11205] | 62 | if(!problemData.TrainingIndices.Any()) return null; // don't create an LR model if the problem does not have a training set (e.g. loaded into an existing model)
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[6642] | 63 |
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| 64 | //clear checked inputVariables
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| 65 | foreach (var inputVariable in problemData.InputVariables.CheckedItems) {
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| 66 | problemData.InputVariables.SetItemCheckedState(inputVariable.Value, false);
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| 67 | }
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| 68 |
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| 69 | //check inputVariables used in the symbolic regression model
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| 70 | var usedVariables =
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| 71 | Content.Model.SymbolicExpressionTree.IterateNodesPostfix().OfType<VariableTreeNode>().Select(
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| 72 | node => node.VariableName).Distinct();
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| 73 | foreach (var variable in usedVariables) {
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| 74 | problemData.InputVariables.SetItemCheckedState(
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[8100] | 75 | problemData.InputVariables.First(x => x.Value == variable), true);
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[6642] | 76 | }
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| 77 |
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| 78 | var solution = LinearRegression.CreateLinearRegressionSolution(problemData, out rmse, out cvRmsError);
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| 79 | solution.Name = "Linear Model";
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| 80 | return solution;
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| 81 | }
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| 82 |
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| 83 | protected override void Content_ModelChanged(object sender, EventArgs e) {
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| 84 | linearRegressionSolution = CreateLinearRegressionSolution();
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| 85 | base.Content_ModelChanged(sender, e);
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| 86 | }
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| 87 |
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| 88 | protected override void Content_ProblemDataChanged(object sender, EventArgs e) {
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| 89 | linearRegressionSolution = CreateLinearRegressionSolution();
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| 90 | base.Content_ProblemDataChanged(sender, e);
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| 91 | }
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| 92 | }
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| 93 | }
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