#region License Information /* HeuristicLab * Copyright (C) 2002-2008 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 System.Collections.Generic; using System.Linq; using System.Text; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.DataAnalysis; namespace HeuristicLab.GP.StructureIdentification { public class MeanSquaredErrorEvaluator : GPEvaluatorBase { public override string Description { get { return @"Evaluates 'FunctionTree' for all samples of 'DataSet' and calculates the mean-squared-error for the estimated values vs. the real values of 'TargetVariable'."; } } public MeanSquaredErrorEvaluator() : base() { AddVariableInfo(new VariableInfo("MSE", "The mean squared error of the model", typeof(DoubleData), VariableKind.New)); } public override void Evaluate(IScope scope, BakedTreeEvaluator evaluator, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) { double errorsSquaredSum = 0; for (int sample = start; sample < end; sample++) { double original = dataset.GetValue(sample, targetVariable); double estimated = evaluator.Evaluate(sample); if (updateTargetValues) { dataset.SetValue(sample, targetVariable, estimated); } if (!double.IsNaN(original) && !double.IsInfinity(original)) { double error = estimated - original; errorsSquaredSum += error * error; } } errorsSquaredSum /= (end - start); if (double.IsNaN(errorsSquaredSum) || double.IsInfinity(errorsSquaredSum)) { errorsSquaredSum = double.MaxValue; } DoubleData mse = GetVariableValue("MSE", scope, false, false); if (mse == null) { mse = new DoubleData(); scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("MSE"), mse)); } mse.Data = errorsSquaredSum; } } }