#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
namespace HeuristicLab.Problems.DataAnalysis {
public class OnlineNormalizedMeanSquaredErrorEvaluator : IOnlineEvaluator {
private OnlineMeanAndVarianceCalculator meanSquaredErrorCalculator;
private OnlineMeanAndVarianceCalculator originalVarianceCalculator;
public double NormalizedMeanSquaredError {
get {
double var = originalVarianceCalculator.Variance;
double m = meanSquaredErrorCalculator.Mean;
return var > 0 ? m / var : 0.0;
}
}
public OnlineNormalizedMeanSquaredErrorEvaluator() {
meanSquaredErrorCalculator = new OnlineMeanAndVarianceCalculator();
originalVarianceCalculator = new OnlineMeanAndVarianceCalculator();
Reset();
}
#region IOnlineEvaluator Members
public double Value {
get { return NormalizedMeanSquaredError; }
}
public void Reset() {
meanSquaredErrorCalculator.Reset();
originalVarianceCalculator.Reset();
}
public void Add(double original, double estimated) {
// no need to check for validity of values explicitly as it is checked in the meanAndVariance calculator anyway
double error = estimated - original;
meanSquaredErrorCalculator.Add(error * error);
originalVarianceCalculator.Add(original);
}
#endregion
public static double Calculate(IEnumerable first, IEnumerable second) {
IEnumerator firstEnumerator = first.GetEnumerator();
IEnumerator secondEnumerator = second.GetEnumerator();
OnlineNormalizedMeanSquaredErrorEvaluator normalizedMSEEvaluator = new OnlineNormalizedMeanSquaredErrorEvaluator();
// always move forward both enumerators (do not use short-circuit evaluation!)
while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
double estimated = secondEnumerator.Current;
double original = firstEnumerator.Current;
normalizedMSEEvaluator.Add(original, estimated);
}
// check if both enumerators are at the end to make sure both enumerations have the same length
if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
} else {
return normalizedMSEEvaluator.NormalizedMeanSquaredError;
}
}
}
}