[5624] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[7259] | 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5624] | 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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[9363] | 34 | public abstract class
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| 35 | SymbolicClassificationModel : SymbolicDataAnalysisModel, ISymbolicClassificationModel {
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| 36 | [Storable]
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| 37 | private double lowerEstimationLimit;
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| 38 | public double LowerEstimationLimit { get { return lowerEstimationLimit; } }
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| 39 | [Storable]
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| 40 | private double upperEstimationLimit;
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| 41 | public double UpperEstimationLimit { get { return upperEstimationLimit; } }
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| 42 |
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[5624] | 43 | [StorableConstructor]
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| 44 | protected SymbolicClassificationModel(bool deserializing) : base(deserializing) { }
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| 45 | protected SymbolicClassificationModel(SymbolicClassificationModel original, Cloner cloner)
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| 46 | : base(original, cloner) {
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[9363] | 47 | lowerEstimationLimit = original.lowerEstimationLimit;
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| 48 | upperEstimationLimit = original.upperEstimationLimit;
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[5624] | 49 | }
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[9363] | 50 | protected SymbolicClassificationModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
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[5624] | 51 | : base(tree, interpreter) {
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[9363] | 52 | this.lowerEstimationLimit = lowerEstimationLimit;
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| 53 | this.upperEstimationLimit = upperEstimationLimit;
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[5624] | 54 | }
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| 55 |
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[9363] | 56 | public abstract IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows);
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| 57 | public abstract void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
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[5624] | 58 |
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[9363] | 59 | public abstract ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
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[6604] | 60 |
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| 61 | IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
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| 62 | return CreateClassificationSolution(problemData);
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| 63 | }
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| 64 |
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[9363] | 65 | public void Scale(IClassificationProblemData problemData) {
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| 66 | Scale(problemData, problemData.TargetVariable);
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| 67 | }
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[5624] | 68 | }
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| 69 | }
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