Changeset 5736 for branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators

Timestamp:

03/17/11 15:14:45 (14 years ago)

Author:

gkronber

Message:

#1418 implemented linear scaling for classification solutions, fixed bugs interactive simplifier view for classification solutions.

Location:

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators

Files:

• AccuracyMaximizationThresholdCalculator.cs (modified) (1 diff)
• NormalDistributionCutPointsThresholdCalculator.cs (modified) (2 diffs)

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators/AccuracyMaximizationThresholdCalculator.cs

@@ -69 +69 @@
       classValues = problemData.ClassValues.OrderBy(x => x).ToArray();
       int nClasses = classValues.Length;
-      thresholds = new double[nClasses + 1];
+      thresholds = new double[nClasses];
       thresholds[0] = double.NegativeInfinity;
-      thresholds[thresholds.Length - 1] = double.PositiveInfinity;
+      // thresholds[thresholds.Length - 1] = double.PositiveInfinity;
 
       // incrementally calculate accuracy of all possible thresholds
       int[,] confusionMatrix = new int[nClasses, nClasses];
 
-      for (int i = 1; i < thresholds.Length - 1; i++) {
+      for (int i = 1; i < thresholds.Length; i++) {
         double lowerThreshold = thresholds[i - 1];
         double actualThreshold = Math.Max(lowerThreshold, minEstimatedValue);

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators/NormalDistributionCutPointsThresholdCalculator.cs

@@ -88 +88 @@
       thresholdList.Sort();
       thresholdList.Insert(0, double.NegativeInfinity);
-      thresholdList.Add(double.PositiveInfinity);
 
       // determine class values for each partition separated by a threshold by calculating the density of all class distributions
       // all points in the partition are classified as the class with the maximal density in the parition
       List<double> classValuesList = new List<double>();
-      for (int i = 0; i < thresholdList.Count - 1; i++) {
+      for (int i = 0; i < thresholdList.Count; i++) {
         double m;
         if (double.IsNegativeInfinity(thresholdList[i])) {
           m = thresholdList[i + 1] - 1.0; // smaller than the smalles non-infinity threshold
-        } else if (double.IsPositiveInfinity(thresholdList[i + 1])) {
-          m = thresholdList[i] + 1.0; // larger than the largest non-infinity threshold
+        } else if (i == thresholdList.Count - 1) {
+          // last threshold
+          m = thresholdList[i] + 1.0; // larger than the last threshold
         } else {
           m = thresholdList[i] + (thresholdList[i + 1] - thresholdList[i]) / 2.0; // middle of partition
@@ -135 +135 @@
         }
       }
-      filteredThresholds.Add(double.PositiveInfinity);
       thresholds = filteredThresholds.ToArray();
       classValues = filteredClassValues.ToArray();