1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | * and the BEACON Center for the Study of Evolution in Action.
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5 | *
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6 | * This file is part of HeuristicLab.
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7 | *
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8 | * HeuristicLab is free software: you can redistribute it and/or modify
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9 | * it under the terms of the GNU General Public License as published by
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10 | * the Free Software Foundation, either version 3 of the License, or
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11 | * (at your option) any later version.
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12 | *
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13 | * HeuristicLab is distributed in the hope that it will be useful,
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14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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16 | * GNU General Public License for more details.
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17 | *
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18 | * You should have received a copy of the GNU General Public License
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19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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20 | */
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21 | #endregion
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22 |
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23 | using System;
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24 | using System.Collections.Generic;
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25 | using System.Diagnostics;
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26 | using System.Linq;
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27 | using HeuristicLab.Common;
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28 |
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29 | namespace HeuristicLab.Algorithms.DataAnalysis {
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30 | // relative error loss is a special case of weighted absolute error loss
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31 | // absolute loss is weighted by (1/target)
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32 | public class RelativeErrorLoss : ILossFunction {
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33 | public double GetLoss(IEnumerable<double> target, IEnumerable<double> pred, IEnumerable<double> weight) {
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34 | var targetEnum = target.GetEnumerator();
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35 | var predEnum = pred.GetEnumerator();
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36 | var weightEnum = weight.GetEnumerator();
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37 |
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38 | double s = 0;
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39 | while (targetEnum.MoveNext() & predEnum.MoveNext() & weightEnum.MoveNext()) {
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40 | double res = targetEnum.Current - predEnum.Current;
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41 | s += weightEnum.Current * Math.Abs(res) * Math.Abs(1.0 / targetEnum.Current);
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42 | }
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43 | if (targetEnum.MoveNext() | predEnum.MoveNext() | weightEnum.MoveNext())
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44 | throw new ArgumentException("target, pred and weight have differing lengths");
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45 |
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46 | return s;
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47 | }
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48 |
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49 | public IEnumerable<double> GetLossGradient(IEnumerable<double> target, IEnumerable<double> pred, IEnumerable<double> weight) {
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50 | var targetEnum = target.GetEnumerator();
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51 | var predEnum = pred.GetEnumerator();
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52 | var weightEnum = weight.GetEnumerator();
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53 |
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54 | while (targetEnum.MoveNext() & predEnum.MoveNext() & weightEnum.MoveNext()) {
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55 | // weight * sign(res) * abs(1 / target)
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56 | var res = targetEnum.Current - predEnum.Current;
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57 | if (res > 0) yield return weightEnum.Current * 1.0 / Math.Abs(targetEnum.Current);
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58 | else if (res < 0) yield return -weightEnum.Current * 1.0 / Math.Abs(targetEnum.Current);
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59 | else yield return 0.0;
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60 | }
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61 | if (targetEnum.MoveNext() | predEnum.MoveNext() | weightEnum.MoveNext())
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62 | throw new ArgumentException("target, pred and weight have differing lengths");
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63 | }
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64 |
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65 | public LineSearchFunc GetLineSearchFunc(IEnumerable<double> target, IEnumerable<double> pred, IEnumerable<double> weight) {
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66 | var targetArr = target.ToArray();
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67 | var predArr = pred.ToArray();
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68 | var weightArr = weight.ToArray();
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69 | Debug.Assert(weightArr.All(w => w.IsAlmost(1.0)));
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70 |
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71 | if (targetArr.Length != predArr.Length || predArr.Length != weightArr.Length)
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72 | throw new ArgumentException("target, pred and weight have differing lengths");
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73 |
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74 | // line search for relative error
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75 | // weighted median (weight = 1/target)
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76 | LineSearchFunc lineSearch = (idx, startIdx, endIdx) => {
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77 | // weighted median calculation
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78 | int nRows = endIdx - startIdx + 1; // startIdx and endIdx are inclusive
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79 | if (nRows == 1) return targetArr[idx[startIdx]] - predArr[idx[startIdx]]; // res
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80 | else if (nRows == 2) {
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81 | // weighted average of two residuals
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82 | var w0 = weightArr[idx[startIdx]] * Math.Abs(1.0 / targetArr[idx[startIdx]]);
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83 | var w1 = weightArr[idx[endIdx]] * Math.Abs(1.0 / targetArr[idx[endIdx]]);
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84 | return (w0 * (targetArr[idx[startIdx]] - predArr[idx[startIdx]]) + w1 * (targetArr[idx[endIdx]] - predArr[idx[endIdx]])) / (w0 + w1);
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85 | } else {
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86 | var ts = from offset in Enumerable.Range(0, nRows)
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87 | let i = startIdx + offset
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88 | let row = idx[i]
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89 | select new { res = targetArr[row] - predArr[row], weight = weightArr[row] * Math.Abs(1.0 / targetArr[row]) };
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90 | ts = ts.OrderBy(t => t.res);
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91 | var totalWeight = ts.Sum(t => t.weight);
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92 | var tsEnumerator = ts.GetEnumerator();
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93 | tsEnumerator.MoveNext();
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94 |
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95 | double aggWeight = tsEnumerator.Current.weight; // weight of first
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96 |
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97 | while (aggWeight < totalWeight / 2) {
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98 | tsEnumerator.MoveNext();
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99 | aggWeight += tsEnumerator.Current.weight;
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100 | }
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101 | return tsEnumerator.Current.res;
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102 | }
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103 | };
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104 | return lineSearch;
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105 | }
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106 |
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107 | public override string ToString() {
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108 | return "Relative error loss";
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109 | }
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110 | }
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111 | }
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