#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Parameters; using HEAL.Attic; namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification { /// /// An operator that analyzes the validation best symbolic classification solution for single objective symbolic classification problems. /// [Item("SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic classification solution for single objective symbolic classification problems.")] [StorableType("4BEB7C5A-0B3A-4276-95C6-689F8BA8E0E6")] public sealed class SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer, ISymbolicDataAnalysisBoundedOperator, ISymbolicClassificationModelCreatorOperator { private const string EstimationLimitsParameterName = "EstimationLimits"; private const string ModelCreatorParameterName = "ModelCreator"; #region parameter properties public IValueLookupParameter EstimationLimitsParameter { get { return (IValueLookupParameter)Parameters[EstimationLimitsParameterName]; } } public IValueLookupParameter ModelCreatorParameter { get { return (IValueLookupParameter)Parameters[ModelCreatorParameterName]; } } ILookupParameter ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter { get { return ModelCreatorParameter; } } #endregion [StorableConstructor] private SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { } private SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { } public SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer() : base() { Parameters.Add(new ValueLookupParameter(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic classification model.")); Parameters.Add(new ValueLookupParameter(ModelCreatorParameterName, "")); } public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(this, cloner); } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { // BackwardsCompatibility3.4 #region Backwards compatible code, remove with 3.5 if (!Parameters.ContainsKey(ModelCreatorParameterName)) Parameters.Add(new ValueLookupParameter(ModelCreatorParameterName, "")); #endregion } protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) { var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper); if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue); model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices); return model.CreateClassificationSolution((IClassificationProblemData)ProblemDataParameter.ActualValue.Clone()); } } }