Changeset 7562 for branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/MedianThresholdCalculator.cs

Timestamp:

03/06/12 15:08:13 (13 years ago)

Author:

sforsten

Message:

#1776:

• bug fix in NeighbourhoodWeightCalculator
• added GetConfidence method to IClassificationEnsembleSolutionWeightCalculator
• adjusted the confidence column in ClassificationEnsembleSolutionEstimatedClassValuesView

File:

• branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/MedianThresholdCalculator.cs (modified) (3 diffs)

branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/MedianThresholdCalculator.cs

@@ -20 +20 @@
 #endregion
 
+using System.Collections;
 using System.Collections.Generic;
 using System.Linq;
@@ -84 +85 @@
       }
       AccuracyMaximizationThresholdCalculator.CalculateThresholds(solutionProblemData[0], median, targetValues, out classValues, out threshold);
-      return median;
+      return Enumerable.Repeat<double>(1, discriminantSolutions.Count());
     }
 
     protected override double DiscriminantAggregateEstimatedClassValues(IDictionary<IClassificationSolution, double> estimatedClassValues, IDictionary<IClassificationSolution, double> estimatedValues) {
-      double classValue = classValues.First();
       IList<double> values = estimatedValues.Select(x => x.Value).ToList();
       if (values.Count <= 0)
         return double.NaN;
       double median = GetMedian(values);
+      return GetClassValueToMedian(median);
+    }
+    private double GetClassValueToMedian(double median) {
+      double classValue = classValues.First();
       for (int i = 0; i < classValues.Count(); i++) {
         if (median > threshold[i])
@@ -100 +104 @@
       }
       return classValue;
+    }
+
+    protected override double GetDiscriminantConfidence(IEnumerable<IDiscriminantFunctionClassificationSolution> solutions, int index, double estimatedClassValue) {
+      // only works with binary classification
+      if (!classValues.Count().Equals(2))
+        return double.NaN;
+      Dataset dataset = solutions.First().ProblemData.Dataset;
+      IList<double> values = solutions.Select(s => s.Model.GetEstimatedValues(dataset, Enumerable.Repeat(index, 1)).First()).ToList();
+      if (values.Count <= 0)
+        return double.NaN;
+      double median = GetMedian(values);
+      if (estimatedClassValue.Equals(classValues[0])) {
+        if (median < estimatedClassValue)
+          return 1;
+        else if (median >= threshold[1])
+          return 0;
+        else {
+          double distance = threshold[1] - classValues[0];
+          return (1 / distance) * (median - classValues[0]);
+        }
+      } else if (estimatedClassValue.Equals(classValues[1])) {
+        if (median > estimatedClassValue)
+          return 1;
+        else if (median <= threshold[1])
+          return 0;
+        else {
+          double distance = classValues[1] - threshold[1];
+          return (1 / distance) * (classValues[1] - median);
+        }
+      } else
+        return double.NaN;
     }