[15124] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17226] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[15124] | 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 HeuristicLab.Common;
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| 23 | using HeuristicLab.Core.Views;
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| 24 | using HeuristicLab.MainForm;
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| 25 | using HeuristicLab.Problems.DataAnalysis;
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| 26 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 27 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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| 28 |
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| 29 | namespace HeuristicLab.Algorithms.DataAnalysis.Views {
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| 30 | [View("Random forest model")]
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| 31 | [Content(typeof(IRandomForestModel), true)]
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| 32 | public partial class RandomForestModelView : ItemView {
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| 33 |
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| 34 | public new IRandomForestModel Content {
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| 35 | get { return (IRandomForestModel)base.Content; }
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| 36 | set { base.Content = value; }
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| 37 | }
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| 38 |
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| 39 | protected override void SetEnabledStateOfControls() {
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| 40 | base.SetEnabledStateOfControls();
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| 41 | listBox.Enabled = Content != null;
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| 42 | viewHost.Enabled = Content != null;
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| 43 | }
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| 44 |
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| 45 | public RandomForestModelView()
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| 46 | : base() {
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| 47 | InitializeComponent();
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| 48 | }
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| 49 |
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| 50 | protected override void OnContentChanged() {
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| 51 | base.OnContentChanged();
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| 52 | if (Content == null) {
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| 53 | viewHost.Content = null;
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| 54 | listBox.Items.Clear();
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| 55 | } else {
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| 56 | viewHost.Content = null;
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| 57 | listBox.Items.Clear();
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| 58 | var rfModel = Content;
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| 59 | var numTrees = rfModel.NumberOfTrees;
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| 60 | for (int i = 0; i < numTrees; i++) {
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| 61 | listBox.Items.Add(i + 1);
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| 62 | }
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| 63 | }
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| 64 | }
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| 65 |
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| 66 | private void listBox_SelectedIndexChanged(object sender, System.EventArgs e) {
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| 67 | if (listBox.SelectedItem == null) viewHost.Content = null;
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| 68 | else {
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| 69 | var idx = (int)listBox.SelectedItem;
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| 70 | viewHost.Content = CreateModel(idx);
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| 71 | }
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| 72 | }
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| 73 |
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| 74 | private void listBox_DoubleClick(object sender, System.EventArgs e) {
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| 75 | var selectedItem = listBox.SelectedItem;
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| 76 | if (selectedItem == null) return;
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| 77 | var idx = (int)listBox.SelectedItem;
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| 78 | MainFormManager.MainForm.ShowContent(CreateModel(idx));
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| 79 | }
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| 80 |
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| 81 | private IContent CreateModel(int idx) {
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| 82 | idx -= 1;
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| 83 | var rfModel = Content;
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| 84 | var rfClassModel = rfModel as IClassificationModel; // rfModel is always a IRegressionModel and a IClassificationModel
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| 85 | var targetVariable = rfClassModel.TargetVariable;
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| 86 | if (rfModel == null) return null;
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| 87 | if (idx < 0 || idx >= rfModel.NumberOfTrees)
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| 88 | return null;
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| 89 | var syModel = new SymbolicRegressionModel(targetVariable, rfModel.ExtractTree(idx),
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| 90 | new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
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| 91 | return syModel;
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| 92 | }
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| 93 | }
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| 94 | }
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