- Timestamp:
- 12/25/11 20:52:38 (12 years ago)
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- 1 edited
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views/3.4/InteractiveSymbolicDiscriminantFunctionClassificationSolutionSimplifierView.cs
r7027 r7233 81 81 double[] thresholds; 82 82 // normal distribution cut points are used as thresholds here because they are a lot faster to calculate than the accuracy maximizing thresholds 83 NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(Content.ProblemData, originalOutput, targetClassValues, out classValues, out thresholds);83 AccuracyMaximizationThresholdCalculator.CalculateThresholds(Content.ProblemData, originalOutput, targetClassValues, out classValues, out thresholds); 84 84 var classifier = new SymbolicDiscriminantFunctionClassificationModel(tree, interpreter); 85 85 classifier.SetThresholdsAndClassValues(thresholds, classValues); … … 96 96 .LimitToRange(Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit) 97 97 .ToArray(); 98 NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(Content.ProblemData, newOutput, targetClassValues, out classValues, out thresholds);98 AccuracyMaximizationThresholdCalculator.CalculateThresholds(Content.ProblemData, newOutput, targetClassValues, out classValues, out thresholds); 99 99 classifier = new SymbolicDiscriminantFunctionClassificationModel(tree, interpreter); 100 100 classifier.SetThresholdsAndClassValues(thresholds, classValues);
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