1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21 


22  using HeuristicLab.Common;


23  using HeuristicLab.Core;


24  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


25  using HeuristicLab.Problems.DataAnalysis;


26 


27  namespace HeuristicLab.Algorithms.DataAnalysis {


28  /// <summary>


29  /// Represents a neural network solution for a regression problem which can be visualized in the GUI.


30  /// </summary>


31  [Item("NeuralNetworkRegressionSolution", "Represents a neural network solution for a regression problem which can be visualized in the GUI.")]


32  [StorableClass]


33  public sealed class NeuralNetworkRegressionSolution : RegressionSolution, INeuralNetworkRegressionSolution {


34 


35  public new INeuralNetworkModel Model {


36  get { return (INeuralNetworkModel)base.Model; }


37  set { base.Model = value; }


38  }


39 


40  [StorableConstructor]


41  private NeuralNetworkRegressionSolution(bool deserializing) : base(deserializing) { }


42  private NeuralNetworkRegressionSolution(NeuralNetworkRegressionSolution original, Cloner cloner)


43  : base(original, cloner) {


44  }


45  public NeuralNetworkRegressionSolution(INeuralNetworkModel nnModel, IRegressionProblemData problemData)


46  : base(nnModel, problemData) {


47  }


48 


49  public override IDeepCloneable Clone(Cloner cloner) {


50  return new NeuralNetworkRegressionSolution(this, cloner);


51  }


52  }


53  }

