Changeset 8550 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicDiscriminantFunctionClassificationModel.cs
- Timestamp:
- 08/31/12 13:52:24 (12 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicDiscriminantFunctionClassificationModel.cs
r8533 r8550 122 122 #endregion 123 123 124 public static void SetAccuracyMaximizingThresholds(IDiscriminantFunctionClassificationModel model,IClassificationProblemData problemData) {124 public void SetAccuracyMaximizingThresholds(IClassificationProblemData problemData) { 125 125 double[] classValues; 126 126 double[] thresholds; 127 127 var targetClassValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices); 128 var estimatedTrainingValues = model.GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices);128 var estimatedTrainingValues = GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices); 129 129 AccuracyMaximizationThresholdCalculator.CalculateThresholds(problemData, estimatedTrainingValues, targetClassValues, out classValues, out thresholds); 130 130 131 model.SetThresholdsAndClassValues(thresholds, classValues);132 } 133 134 public static void SetClassDistributionCutPointThresholds(IDiscriminantFunctionClassificationModel model,IClassificationProblemData problemData) {131 SetThresholdsAndClassValues(thresholds, classValues); 132 } 133 134 public void SetClassDistributionCutPointThresholds(IClassificationProblemData problemData) { 135 135 double[] classValues; 136 136 double[] thresholds; 137 137 var targetClassValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices); 138 var estimatedTrainingValues = model.GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices);138 var estimatedTrainingValues = GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices); 139 139 NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(problemData, estimatedTrainingValues, targetClassValues, out classValues, out thresholds); 140 140 141 model.SetThresholdsAndClassValues(thresholds, classValues);141 SetThresholdsAndClassValues(thresholds, classValues); 142 142 } 143 143
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