Changeset 5332 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic

Timestamp:

01/19/11 15:48:45 (14 years ago)

Author:

mkommend

Message:

Corrected thresholds classification to maximize the borders between the classes according to the misclassification matrix (ticket #1383).

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/SymbolicClassificationSolution.cs (modified) (3 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/SymbolicClassificationSolution.cs

@@ -111 +111 @@
         double thresholdIncrement = (originalClasses[i] - originalClasses[i - 1]) / slices;
 
-        double bestThreshold = double.NaN;
+        double lowestBestThreshold = double.NaN;
+        double highestBestThreshold = double.NaN;
         double bestClassificationScore = double.PositiveInfinity;
 
@@ -130 +131 @@
             else {
               if (estimatedTarget.Key > lowerThreshold && estimatedTarget.Key < actualThreshold)
+                //false positive
                 classificationScore += ProblemData.MisclassificationMatrix[i - 1, i];
               else
@@ -138 +140 @@
           if (classificationScore < bestClassificationScore) {
             bestClassificationScore = classificationScore;
-            bestThreshold = actualThreshold;
-          }
+            lowestBestThreshold = actualThreshold;
+            highestBestThreshold = actualThreshold;
+          } else if (Math.Abs(classificationScore - bestClassificationScore) < double.Epsilon)
+            highestBestThreshold = actualThreshold;
+
           actualThreshold += thresholdIncrement;
         }
-        thresholds[i] = bestThreshold;
+        double falseNegativePenalty = ProblemData.MisclassificationMatrix[i, i - 1];
+        double falsePositivePenalty = ProblemData.MisclassificationMatrix[i - 1, i];
+        thresholds[i] = (lowestBestThreshold * falsePositivePenalty + highestBestThreshold * falseNegativePenalty) / (falseNegativePenalty + falsePositivePenalty);
       }
       this.optimalThresholds = new List<double>(thresholds);