1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022008 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 System.Collections.Generic;


24  using System.Linq;


25  using System.Text;


26  using HeuristicLab.Core;


27  using HeuristicLab.Data;


28  using HeuristicLab.Operators;


29  using HeuristicLab.DataAnalysis;


30 


31  namespace HeuristicLab.GP.StructureIdentification {


32  public class MeanAbsolutePercentageOfRangeErrorEvaluator : GPEvaluatorBase {


33  public override string Description {


34  get {


35  return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates


36  the mean of the absolute percentage error (scale invariant) relative to the range of the target varibale of estimated values vs. real values of 'TargetVariable'.";


37  }


38  }


39 


40  public MeanAbsolutePercentageOfRangeErrorEvaluator()


41  : base() {


42  AddVariableInfo(new VariableInfo("MAPRE", "The mean absolute percentage range error of the model", typeof(DoubleData), VariableKind.New));


43  }


44 


45  public override void Evaluate(IScope scope, BakedTreeEvaluator evaluator, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {


46  double errorsSum = 0.0;


47  int n = 0;


48  double range = dataset.GetRange(targetVariable, start, end);


49  for (int sample = start; sample < end; sample++) {


50  double estimated = evaluator.Evaluate(sample);


51  double original = dataset.GetValue(sample, targetVariable);


52 


53  if (updateTargetValues) {


54  dataset.SetValue(sample, targetVariable, estimated);


55  }


56 


57  if (!double.IsNaN(original) && !double.IsInfinity(original) && original != 0.0) {


58  double percent_error = Math.Abs((estimated  original) / range);


59  errorsSum += percent_error;


60  n++;


61  }


62  }


63  double quality = errorsSum / n;


64  if (double.IsNaN(quality)  double.IsInfinity(quality))


65  quality = double.MaxValue;


66 


67  // create a variable for the MAPRE


68  DoubleData mapre = GetVariableValue<DoubleData>("MAPRE", scope, false, false);


69  if (mapre == null) {


70  mapre = new DoubleData();


71  scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("MAPRE"), mapre));


72  }


73 


74  mapre.Data = quality;


75  }


76  }


77  }

