[5624] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[9456] | 3 | * Copyright (C) 2002-2013 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 HeuristicLab.Common;
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| 23 | using HeuristicLab.Core;
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| 24 | using HeuristicLab.Data;
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[6411] | 25 | using HeuristicLab.Optimization;
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[5624] | 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 solution (model + data) and attributes of the solution like accuracy and complexity
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| 31 | /// </summary>
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| 32 | [StorableClass]
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| 33 | [Item(Name = "SymbolicClassificationSolution", Description = "Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity.")]
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[5717] | 34 | public sealed class SymbolicClassificationSolution : ClassificationSolution, ISymbolicClassificationSolution {
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[5736] | 35 | private const string ModelLengthResultName = "ModelLength";
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| 36 | private const string ModelDepthResultName = "ModelDepth";
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[5624] | 37 |
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| 38 | public new ISymbolicClassificationModel Model {
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| 39 | get { return (ISymbolicClassificationModel)base.Model; }
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[5717] | 40 | set { base.Model = value; }
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[5624] | 41 | }
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| 42 |
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| 43 | ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
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| 44 | get { return (ISymbolicDataAnalysisModel)base.Model; }
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| 45 | }
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[5736] | 46 | public int ModelLength {
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| 47 | get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
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| 48 | private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
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| 49 | }
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[5624] | 50 |
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[5736] | 51 | public int ModelDepth {
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| 52 | get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
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| 53 | private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
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| 54 | }
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| 55 |
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[5624] | 56 | [StorableConstructor]
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[5717] | 57 | private SymbolicClassificationSolution(bool deserializing) : base(deserializing) { }
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| 58 | private SymbolicClassificationSolution(SymbolicClassificationSolution original, Cloner cloner)
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[5624] | 59 | : base(original, cloner) {
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| 60 | }
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| 61 | public SymbolicClassificationSolution(ISymbolicClassificationModel model, IClassificationProblemData problemData)
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| 62 | : base(model, problemData) {
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[5736] | 63 | Add(new Result(ModelLengthResultName, "Length of the symbolic classification model.", new IntValue()));
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| 64 | Add(new Result(ModelDepthResultName, "Depth of the symbolic classification model.", new IntValue()));
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[6589] | 65 | RecalculateResults();
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[5624] | 66 | }
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| 67 |
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| 68 | public override IDeepCloneable Clone(Cloner cloner) {
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| 69 | return new SymbolicClassificationSolution(this, cloner);
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| 70 | }
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[5736] | 71 |
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[6411] | 72 | protected override void RecalculateResults() {
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[8723] | 73 | base.RecalculateResults();
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[5736] | 74 | ModelLength = Model.SymbolicExpressionTree.Length;
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| 75 | ModelDepth = Model.SymbolicExpressionTree.Depth;
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| 76 | }
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[5624] | 77 | }
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| 78 | }
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