1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2019 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 HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HEAL.Attic;
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25 | using HeuristicLab.Problems.DataAnalysis;
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26 |
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27 | namespace HeuristicLab.Algorithms.DataAnalysis {
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28 | /// <summary>
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29 | /// Represents a neural network solution for a classification problem which can be visualized in the GUI.
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30 | /// </summary>
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31 | [Item("NeuralNetworkClassificationSolution", "Represents a neural network solution for a classification problem which can be visualized in the GUI.")]
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32 | [StorableType("7B08B27F-66B6-47C8-946E-51B28F603B43")]
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33 | public sealed class NeuralNetworkClassificationSolution : ClassificationSolution, INeuralNetworkClassificationSolution {
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34 |
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35 | public new INeuralNetworkModel Model {
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36 | get { return (INeuralNetworkModel)base.Model; }
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37 | set { base.Model = value; }
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38 | }
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39 |
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40 | [StorableConstructor]
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41 | private NeuralNetworkClassificationSolution(StorableConstructorFlag _) : base(_) { }
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42 | private NeuralNetworkClassificationSolution(NeuralNetworkClassificationSolution original, Cloner cloner)
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43 | : base(original, cloner) {
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44 | }
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45 | public NeuralNetworkClassificationSolution(INeuralNetworkModel nnModel, IClassificationProblemData problemData)
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46 | : base(nnModel, problemData) {
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47 | }
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48 |
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49 | public override IDeepCloneable Clone(Cloner cloner) {
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50 | return new NeuralNetworkClassificationSolution(this, cloner);
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51 | }
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52 |
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53 | }
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54 | }
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