#region License Information /* HeuristicLab * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Linq; using System.Windows.Forms; using HeuristicLab.Algorithms.DataAnalysis; using HeuristicLab.MainForm; using HeuristicLab.Problems.DataAnalysis.OnlineCalculators; namespace HeuristicLab.Problems.DataAnalysis.Views.Classification { [View("Solution Comparison")] [Content(typeof(IClassificationSolution))] public partial class ClassificationSolutionComparisonView : DataAnalysisSolutionEvaluationView { private List solutions; public ClassificationSolutionComparisonView() { InitializeComponent(); } public new IClassificationSolution Content { get { return (IClassificationSolution)base.Content; } set { base.Content = value; } } protected override void RegisterContentEvents() { base.RegisterContentEvents(); Content.ModelChanged += new EventHandler(Content_ModelChanged); Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged); } protected override void DeregisterContentEvents() { base.DeregisterContentEvents(); Content.ModelChanged -= new EventHandler(Content_ModelChanged); Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged); } protected virtual void Content_ModelChanged(object sender, EventArgs e) { if (InvokeRequired) Invoke((Action)Content_ModelChanged, sender, e); else UpdateDataGridView(); } protected virtual void Content_ProblemDataChanged(object sender, EventArgs e) { if (InvokeRequired) Invoke((Action)Content_ProblemDataChanged, sender, e); else { UpdateDataGridView(); } } protected override void OnContentChanged() { base.OnContentChanged(); UpdateDataGridView(); } private void UpdateDataGridView() { if (InvokeRequired) { Invoke((Action)UpdateDataGridView); } else { if (Content == null) { dataGridView.Rows.Clear(); dataGridView.Columns.Clear(); solutions = null; } else { IClassificationProblemData problemData = Content.ProblemData; solutions = new List() { Content }; solutions.AddRange(GenerateClassificationSolutions().OrderBy(s=>s.Name)); dataGridView.ColumnCount = 4; dataGridView.RowCount = solutions.Count(); dataGridView.Columns[0].HeaderText = "Accuracy (training)"; dataGridView.Columns[1].HeaderText = "Accuracy (test)"; dataGridView.Columns[2].HeaderText = "Matthews Correlation Coefficient (training)"; dataGridView.Columns[3].HeaderText = "Matthews Correlation Coefficient (test)"; if (problemData.Classes == 2) { dataGridView.ColumnCount = 6; dataGridView.Columns[4].HeaderText = "F1 Score (training)"; dataGridView.Columns[5].HeaderText = "F1 Score (test)"; } for (int row = 0; row < solutions.Count; row++) { var solution = solutions[row]; dataGridView.Rows[row].HeaderCell.Value = solution.Name; dataGridView[0, row].Value = solution.TrainingAccuracy; dataGridView[1, row].Value = solution.TestAccuracy; var trainingIndizes = problemData.TrainingIndices; var originalTrainingValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, trainingIndizes); var estimatedTrainingValues = solution.EstimatedTrainingClassValues; var testIndices = problemData.TestIndices; var originalTestValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, testIndices); var estimatedTestValues = solution.EstimatedTestClassValues; OnlineCalculatorError errorState; dataGridView[2, row].Value = MatthewsCorrelationCoefficientCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState); dataGridView[3, row].Value = MatthewsCorrelationCoefficientCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState); if (problemData.Classes == 2) { dataGridView[4, row].Value = FOneScoreCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState); dataGridView[5, row].Value = FOneScoreCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState); } } dataGridView.AutoResizeColumns(DataGridViewAutoSizeColumnsMode.ColumnHeader); dataGridView.AutoResizeRowHeadersWidth(DataGridViewRowHeadersWidthSizeMode.AutoSizeToAllHeaders); } } } protected virtual IEnumerable GenerateClassificationSolutions() { var problemData = Content.ProblemData; var newSolutions = new List(); var zeroR = ZeroR.CreateZeroRSolution(problemData); zeroR.Name = "ZeroR Classification Solution"; newSolutions.Add(zeroR); try { var oneR = OneR.CreateOneRSolution(problemData); oneR.Name = "OneR Classification Solution (all variables)"; newSolutions.Add(oneR); } catch (NotSupportedException) { } catch (ArgumentException) { } try { var lda = LinearDiscriminantAnalysis.CreateLinearDiscriminantAnalysisSolution(problemData); lda.Name = "Linear Discriminant Analysis Solution (all variables)"; newSolutions.Add(lda); } catch (NotSupportedException) { } catch (ArgumentException) { } return newSolutions; } private void dataGridView_MouseDoubleClick(object sender, MouseEventArgs e) { var hittestinfo = dataGridView.HitTest(e.X, e.Y); if (hittestinfo.Type != DataGridViewHitTestType.RowHeader) { return; } if (hittestinfo.RowIndex > solutions.Count) { return; } MainFormManager.MainForm.ShowContent(solutions[hittestinfo.RowIndex]); } } }