[4022] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 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 |
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| 24 | namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
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| 25 | public class OnlineNormalizedMeanSquaredErrorEvaluator : IOnlineEvaluator {
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| 26 | private OnlineMeanAndVarianceCalculator meanSquaredErrorCalculator;
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| 27 | private OnlineMeanAndVarianceCalculator originalVarianceCalculator;
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| 28 |
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| 29 | public double NormalizedMeanSquaredError {
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| 30 | get {
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| 31 | return meanSquaredErrorCalculator.Mean / originalVarianceCalculator.Variance;
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| 32 | }
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| 33 | }
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| 34 |
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| 35 | public OnlineNormalizedMeanSquaredErrorEvaluator() {
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| 36 | meanSquaredErrorCalculator = new OnlineMeanAndVarianceCalculator();
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| 37 | originalVarianceCalculator = new OnlineMeanAndVarianceCalculator();
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| 38 | Reset();
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| 39 | }
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| 40 |
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| 41 | #region IOnlineEvaluator Members
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| 42 | public double Value {
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| 43 | get { return NormalizedMeanSquaredError; }
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| 44 | }
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| 45 |
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| 46 | public void Reset() {
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| 47 | meanSquaredErrorCalculator.Reset();
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| 48 | originalVarianceCalculator.Reset();
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| 49 | }
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| 50 |
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| 51 | public void Add(double original, double estimated) {
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| 52 | if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
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| 53 | double.IsNaN(original) || double.IsInfinity(original)) {
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| 54 | throw new ArgumentException("Mean squared error is not defined for NaN or infinity elements");
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| 55 | } else {
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| 56 | double error = estimated - original;
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| 57 | meanSquaredErrorCalculator.Add(error * error);
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| 58 | originalVarianceCalculator.Add(original);
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| 59 | }
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| 60 | }
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| 61 | #endregion
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| 62 | }
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| 63 | }
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