[5649] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2011 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.Collections.Generic;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Operators;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Optimization;
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| 31 | using System;
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| 32 |
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| 33 | namespace HeuristicLab.Problems.DataAnalysis {
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| 34 | /// <summary>
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| 35 | /// Represents a classification solution that uses a discriminant function and classification thresholds.
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| 36 | /// </summary>
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| 37 | [StorableClass]
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| 38 | [Item("DiscriminantFunctionClassificationSolution", "Represents a classification solution that uses a discriminant function and classification thresholds.")]
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| 39 | public class DiscriminantFunctionClassificationSolution : ClassificationSolution, IDiscriminantFunctionClassificationSolution {
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| 40 | [StorableConstructor]
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| 41 | protected DiscriminantFunctionClassificationSolution(bool deserializing) : base(deserializing) { }
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| 42 | protected DiscriminantFunctionClassificationSolution(DiscriminantFunctionClassificationSolution original, Cloner cloner)
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| 43 | : base(original, cloner) {
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| 44 | }
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| 45 | public DiscriminantFunctionClassificationSolution(IRegressionModel model, IClassificationProblemData problemData)
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| 46 | : this(new DiscriminantFunctionClassificationModel(model, problemData.ClassValues), problemData) {
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| 47 | }
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| 48 | public DiscriminantFunctionClassificationSolution(IDiscriminantFunctionClassificationModel model, IClassificationProblemData problemData)
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| 49 | : base(model, problemData) {
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| 50 | Model.ThresholdsChanged += new EventHandler(Model_ThresholdsChanged);
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| 51 | }
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| 52 |
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| 53 | #region IDiscriminantFunctionClassificationSolution Members
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| 54 |
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| 55 | public new IDiscriminantFunctionClassificationModel Model {
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| 56 | get { return (IDiscriminantFunctionClassificationModel)base.Model; }
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| 57 | }
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| 58 |
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| 59 | public IEnumerable<double> EstimatedValues {
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| 60 | get { return GetEstimatedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
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| 61 | }
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| 62 |
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| 63 | public IEnumerable<double> EstimatedTrainingValues {
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| 64 | get { return GetEstimatedValues(ProblemData.TrainingIndizes); }
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| 65 | }
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| 66 |
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| 67 | public IEnumerable<double> EstimatedTestValues {
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| 68 | get { return GetEstimatedValues(ProblemData.TestIndizes); }
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| 69 | }
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| 70 |
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| 71 | public IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows) {
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| 72 | return Model.GetEstimatedValues(ProblemData.Dataset, rows);
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| 73 | }
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| 74 |
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| 75 | public IEnumerable<double> Thresholds {
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| 76 | get { return Model.Thresholds; }
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| 77 | }
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| 78 |
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| 79 | public event EventHandler ThresholdsChanged;
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| 80 |
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| 81 | private void Model_ThresholdsChanged(object sender, EventArgs e) {
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| 82 | OnThresholdsChanged(e);
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| 83 | }
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| 84 |
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| 85 | protected virtual void OnThresholdsChanged(EventArgs e) {
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| 86 | var listener = ThresholdsChanged;
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| 87 | if (listener != null) listener(this, e);
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| 88 | }
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| 89 | #endregion
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| 90 | }
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| 91 | }
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