Changeset 7183 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs

Timestamp:

12/13/11 13:52:22 (12 years ago)

Author:

gkronber

Message:

#1081 implemented remaining metrics for time series prognosis solutions, added estimation limits fixed training and validation best solution analyzers, implemented overfitting analyzer.

File:

• branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs (modified) (1 diff)

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs

@@ -93 +93 @@
         meanCalculator.Add(calc.MeanSquaredError);
       }
-      //int i = 0;
-      //foreach (var targetVariable in problemData.TargetVariables) {
-      //  var predictedContinuations = allPredictedContinuations.Select(v => v.ElementAt(i));
-      //  for (int h = 0; h < horizon; h++) {
-      //    OnlineCalculatorError errorState;
-      //    meanCalculator.Add(OnlineMeanSquaredErrorCalculator.Calculate(predictedContinuations
-      //                                                                    .Select(x => x.ElementAt(h))
-      //                                                                    .LimitToRange(lowerEstimationLimit,
-      //                                                                                  upperEstimationLimit),
-      //                                                                  actualContinuations.Select(x => x.ElementAt(h)),
-      //                                                                  out errorState));
-      //    if (errorState != OnlineCalculatorError.None) return double.NaN;
-      //  }
-      //}
+
       return meanCalculator.MeanErrorState == OnlineCalculatorError.None ? meanCalculator.Mean : double.MaxValue;
     }