1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 |
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31 | namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
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32 | public class SimpleMSEEvaluator : SimpleEvaluator {
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33 |
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34 | public ILookupParameter<DoubleValue> MeanSquaredErrorParameter {
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35 | get { return (ILookupParameter<DoubleValue>)Parameters["MeanSquaredError"]; }
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36 | }
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37 |
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38 | [StorableConstructor]
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39 | protected SimpleMSEEvaluator(bool deserializing) : base(deserializing) { }
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40 | protected SimpleMSEEvaluator(SimpleMSEEvaluator original, Cloner cloner)
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41 | : base(original, cloner) {
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42 | }
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43 | public override IDeepCloneable Clone(Cloner cloner) {
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44 | return new SimpleMSEEvaluator(this, cloner);
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45 | }
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46 | public SimpleMSEEvaluator() {
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47 | Parameters.Add(new LookupParameter<DoubleValue>("MeanSquaredError", "The mean squared error of estimated values."));
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48 | }
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49 |
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50 | protected override void Apply(DoubleMatrix values) {
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51 | MeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(values));
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52 | }
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53 |
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54 | public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
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55 | var onlineMseEvaluator = new OnlineMeanSquaredErrorEvaluator();
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56 | var originalEnumerator = original.GetEnumerator();
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57 | var estimatedEnumerator = estimated.GetEnumerator();
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58 | while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
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59 | double e = estimatedEnumerator.Current;
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60 | double o = originalEnumerator.Current;
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61 | onlineMseEvaluator.Add(o, e);
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62 | }
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63 | if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
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64 | throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
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65 | } else {
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66 | return onlineMseEvaluator.MeanSquaredError;
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67 | }
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68 | }
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69 |
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70 | public static double Calculate(DoubleMatrix values) {
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71 | var original = from row in Enumerable.Range(0, values.Rows)
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72 | select values[row, ORIGINAL_INDEX];
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73 | var estimated = from row in Enumerable.Range(0, values.Rows)
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74 | select values[row, ESTIMATION_INDEX];
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75 | return Calculate(original, estimated);
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76 | }
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77 | }
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78 | }
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