1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 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 HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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27 |
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28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
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29 | /// <summary>
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30 | /// Represents a symbolic classification model
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31 | /// </summary>
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32 | [StorableClass]
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33 | [Item(Name = "SymbolicClassificationModel", Description = "Represents a symbolic classification model.")]
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34 | public abstract class SymbolicClassificationModel : SymbolicDataAnalysisModel, ISymbolicClassificationModel {
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35 | [Storable]
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36 | private readonly string targetVariable;
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37 | public string TargetVariable {
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38 | get { return targetVariable; }
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39 | }
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40 |
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41 | [StorableConstructor]
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42 | protected SymbolicClassificationModel(bool deserializing)
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43 | : base(deserializing) {
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44 | targetVariable = string.Empty;
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45 | }
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46 |
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47 | protected SymbolicClassificationModel(SymbolicClassificationModel original, Cloner cloner)
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48 | : base(original, cloner) {
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49 | targetVariable = original.targetVariable;
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50 | }
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51 |
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52 | protected SymbolicClassificationModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
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53 | : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) {
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54 | this.targetVariable = targetVariable;
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55 | }
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56 |
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57 | public abstract IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows);
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58 | public abstract void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
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59 |
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60 | public abstract ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
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61 |
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62 | IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
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63 | return CreateClassificationSolution(problemData);
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64 | }
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65 |
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66 | public void Scale(IClassificationProblemData problemData) {
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67 | Scale(problemData, problemData.TargetVariable);
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68 | }
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69 | }
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70 | }
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