1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  * and the BEACON Center for the Study of Evolution in Action.


5  *


6  * This file is part of HeuristicLab.


7  *


8  * HeuristicLab is free software: you can redistribute it and/or modify


9  * it under the terms of the GNU General Public License as published by


10  * the Free Software Foundation, either version 3 of the License, or


11  * (at your option) any later version.


12  *


13  * HeuristicLab is distributed in the hope that it will be useful,


14  * but WITHOUT ANY WARRANTY; without even the implied warranty of


15  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


16  * GNU General Public License for more details.


17  *


18  * You should have received a copy of the GNU General Public License


19  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


20  */


21  #endregion


22 


23  using System;


24  using System.Collections.Generic;


25  using HeuristicLab.Common;


26  using HeuristicLab.Core;


27  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


28 


29  namespace HeuristicLab.Algorithms.DataAnalysis {


30  // loss function for the weighted absolute error


31  [StorableClass]


32  [Item("Absolute error loss", "")]


33  public sealed class AbsoluteErrorLoss : Item, ILossFunction {


34  public AbsoluteErrorLoss() { }


35 


36  public double GetLoss(IEnumerable<double> target, IEnumerable<double> pred) {


37  var targetEnum = target.GetEnumerator();


38  var predEnum = pred.GetEnumerator();


39 


40  double s = 0;


41  while (targetEnum.MoveNext() & predEnum.MoveNext()) {


42  double res = targetEnum.Current  predEnum.Current;


43  s += Math.Abs(res); // res


44  }


45  if (targetEnum.MoveNext()  predEnum.MoveNext())


46  throw new ArgumentException("target and pred have differing lengths");


47 


48  return s;


49  }


50 


51  public IEnumerable<double> GetLossGradient(IEnumerable<double> target, IEnumerable<double> pred) {


52  var targetEnum = target.GetEnumerator();


53  var predEnum = pred.GetEnumerator();


54 


55  while (targetEnum.MoveNext() & predEnum.MoveNext()) {


56  // dL(y, f(x)) / df(x) = sign(res)


57  var res = targetEnum.Current  predEnum.Current;


58  if (res > 0) yield return 1.0;


59  else if (res < 0) yield return 1.0;


60  else yield return 0.0;


61  }


62  if (targetEnum.MoveNext()  predEnum.MoveNext())


63  throw new ArgumentException("target and pred have differing lengths");


64  }


65 


66  // return median of residuals


67  // targetArr and predArr are not changed by LineSearch


68  public double LineSearch(double[] targetArr, double[] predArr, int[] idx, int startIdx, int endIdx) {


69  if (targetArr.Length != predArr.Length)


70  throw new ArgumentException("target and pred have differing lengths");


71 


72  // Median() is allocating an array anyway


73  // It would be possible to preallocated an array for the residuals if Median() would allow specification of a subrange


74  int nRows = endIdx  startIdx + 1;


75  var res = new double[nRows];


76  for (int i = startIdx; i <= endIdx; i++) {


77  var row = idx[i];


78  res[i  startIdx] = targetArr[row]  predArr[row];


79  }


80  return res.Median(); // TODO: improve efficiency


81  }


82 


83  #region item implementation


84  [StorableConstructor]


85  private AbsoluteErrorLoss(bool deserializing) : base(deserializing) { }


86 


87  private AbsoluteErrorLoss(AbsoluteErrorLoss original, Cloner cloner) : base(original, cloner) { }


88 


89  public override IDeepCloneable Clone(Cloner cloner) {


90  return new AbsoluteErrorLoss(this, cloner);


91  }


92  #endregion


93  }


94  }

