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 System;


23  using HeuristicLab.Common;


24  using HeuristicLab.Core;


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


26  using HeuristicLab.Problems.DataAnalysis;


27  using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;


28 


29  namespace HeuristicLab.Algorithms.DataAnalysis {


30  /// <summary>


31  /// Represents a random forest solution for a regression problem which can be visualized in the GUI.


32  /// </summary>


33  [Item("RandomForestRegressionSolution", "Represents a random forest solution for a regression problem which can be visualized in the GUI.")]


34  [StorableClass]


35  public sealed class RandomForestRegressionSolution : ConfidenceRegressionSolution, IRandomForestRegressionSolution {


36 


37  public new IRandomForestModel Model {


38  get { return (IRandomForestModel)base.Model; }


39  set { base.Model = value; }


40  }


41 


42  public int NumberOfTrees {


43  get { return Model.NumberOfTrees; }


44  }


45 


46  [StorableConstructor]


47  private RandomForestRegressionSolution(bool deserializing) : base(deserializing) { }


48  private RandomForestRegressionSolution(RandomForestRegressionSolution original, Cloner cloner)


49  : base(original, cloner) {


50  }


51  public RandomForestRegressionSolution(IRandomForestModel randomForestModel, IRegressionProblemData problemData)


52  : base(randomForestModel, problemData) {


53  }


54 


55  public override IDeepCloneable Clone(Cloner cloner) {


56  return new RandomForestRegressionSolution(this, cloner);


57  }


58  }


59  }

