#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
[Item("SymbolicRegressionPruningAnalyzer", "An analyzer that prunes introns from the population.")]
[StorableClass]
public sealed class SymbolicRegressionPruningAnalyzer : SymbolicDataAnalysisSingleObjectivePruningAnalyzer {
private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
private const string PruningOperatorParameterName = "PruningOperator";
private SymbolicRegressionPruningAnalyzer(SymbolicRegressionPruningAnalyzer original, Cloner cloner)
: base(original, cloner) {
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SymbolicRegressionPruningAnalyzer(this, cloner);
}
[StorableConstructor]
private SymbolicRegressionPruningAnalyzer(bool deserializing) : base(deserializing) { }
public SymbolicRegressionPruningAnalyzer() {
Parameters.Add(new ValueParameter(ImpactValuesCalculatorParameterName, "The impact values calculator", new SymbolicRegressionSolutionImpactValuesCalculator()));
Parameters.Add(new ValueParameter(PruningOperatorParameterName, "The operator used to prune trees", new SymbolicRegressionPruningOperator()));
}
}
}