Changeset 7100 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveProblem.cs
- Timestamp:
- 11/29/11 20:05:38 (12 years ago)
- Location:
- branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4
- Files:
-
- 2 edited
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- Unmodified
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- Removed
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branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4
- Property svn:ignore
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old new 3 3 HeuristicLabProblemsDataAnalysisSymbolicTimeSeriesPrognosisPlugin.cs 4 4 obj 5 Plugin.cs
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- Property svn:ignore
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branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveProblem.cs
r7099 r7100 69 69 UpdateEstimationLimits(); 70 70 } 71 71 72 72 private void ConfigureGrammarSymbols() { 73 73 var grammar = SymbolicExpressionTreeGrammar as TypeCoherentExpressionGrammar; … … 77 77 private void InitializeOperators() { 78 78 Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveTrainingBestSolutionAnalyzer()); 79 Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveValidationBestSolutionAnalyzer());80 Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveOverfittingAnalyzer());79 //Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveValidationBestSolutionAnalyzer()); 80 //Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveOverfittingAnalyzer()); 81 81 ParameterizeOperators(); 82 82 } 83 83 84 84 private void UpdateEstimationLimits() { 85 if (ProblemData.TrainingIndizes.Any()) {86 var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToList();87 var mean = targetValues.Average();88 var range = targetValues.Max() - targetValues.Min();89 EstimationLimits.Upper = mean + PunishmentFactor * range;90 EstimationLimits.Lower = mean - PunishmentFactor * range;91 } else {92 93 94 }85 //if (ProblemData.TrainingIndizes.Any()) { 86 // var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariables, ProblemData.TrainingIndizes).ToList(); 87 // var mean = targetValues.Average(); 88 // var range = targetValues.Max() - targetValues.Min(); 89 // EstimationLimits.Upper = mean + PunishmentFactor * range; 90 // EstimationLimits.Lower = mean - PunishmentFactor * range; 91 //} else { 92 EstimationLimits.Upper = double.MaxValue; 93 EstimationLimits.Lower = double.MinValue; 94 //} 95 95 } 96 96
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