#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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 System; using HEAL.Attic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Parameters; using HeuristicLab.Problems.DataAnalysis; // ReSharper disable once CheckNamespace namespace HeuristicLab.Algorithms.EGO { [StorableType("94ac7c83-b4ae-4d81-ab55-0db37b5f8155")] [Item("MinimalQuantileCriterium", "Adding or Subtracting the variance * factor to the model estimation")] public class MinimalQuantileCriterium : InfillCriterionBase { #region ParameterNames private const string ConfidenceWeightParameterName = "ConfidenceWeight"; #endregion #region ParameterProperties public IFixedValueParameter ConfidenceWeightParameter => Parameters[ConfidenceWeightParameterName] as IFixedValueParameter; #endregion #region Properties private double ConfidenceWeight => ConfidenceWeightParameter.Value.Value; #endregion #region Constructors, Serialization and Cloning [StorableConstructor] protected MinimalQuantileCriterium(StorableConstructorFlag deserializing) : base(deserializing) { } protected MinimalQuantileCriterium(MinimalQuantileCriterium original, Cloner cloner) : base(original, cloner) { } public MinimalQuantileCriterium() { Parameters.Add(new FixedValueParameter(ConfidenceWeightParameterName, "A value greater than 0. The larger the value the stronger the emphasis on exploration", new DoubleValue(0.5))); } public override IDeepCloneable Clone(Cloner cloner) { return new MinimalQuantileCriterium(this, cloner); } #endregion public override double Evaluate(RealVector vector) { var model = RegressionSolution.Model as IConfidenceRegressionModel; var yhat = model.GetEstimation(vector); var s = Math.Sqrt(model.GetVariance(vector)) * ConfidenceWeight; return (ExpensiveMaximization ? yhat : -yhat) + s; } public override void Initialize() { var model = RegressionSolution.Model as IConfidenceRegressionModel; if (model == null) throw new ArgumentException("can not calculate EI without confidence measure"); } } }