1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022010 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.Common;


27  using HeuristicLab.Core;


28  using HeuristicLab.Data;


29  using HeuristicLab.Parameters;


30 


31  namespace HeuristicLab.Problems.DataAnalysis.Evaluators {


32  public class SimpleNMSEEvaluator : SimpleEvaluator {


33 


34  public ILookupParameter<DoubleValue> NormalizedMeanSquaredErrorParameter {


35  get { return (ILookupParameter<DoubleValue>)Parameters["NormalizedMeanSquaredError"]; }


36  }


37 


38  public SimpleNMSEEvaluator() {


39  Parameters.Add(new LookupParameter<DoubleValue>("NormalizedMeanSquaredError", "The normalized mean squared error (divided by variance) of estimated values."));


40  }


41 


42  protected override void Apply(DoubleMatrix values) {


43  var original = from i in Enumerable.Range(0, values.Rows)


44  select values[i, ORIGINAL_INDEX];


45  var estimated = from i in Enumerable.Range(0, values.Rows)


46  select values[i, ESTIMATION_INDEX];


47 


48  NormalizedMeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(original, estimated));


49  }


50 


51  public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {


52  double mse = SimpleMSEEvaluator.Calculate(original, estimated);


53  return mse / original.Variance();


54  }


55  }


56  }

