Changeset 6961 for trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Timestamp:

11/08/11 10:13:21 (13 years ago)

Author:

mkommend

Message:

#1670: Corrected calculation of DataAnalysisSolution results and modified online calculators to have more meaningful parameter names.

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Files:

• ClassificationSolutionBase.cs (modified) (1 diff)
• DiscriminantFunctionClassificationSolutionBase.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolutionBase.cs

@@ -84 +84 @@
 
       OnlineCalculatorError errorState;
-      double trainingAccuracy = OnlineAccuracyCalculator.Calculate(estimatedTrainingClassValues, originalTrainingClassValues, out errorState);
+      double trainingAccuracy = OnlineAccuracyCalculator.Calculate(originalTrainingClassValues, estimatedTrainingClassValues, out errorState);
       if (errorState != OnlineCalculatorError.None) trainingAccuracy = double.NaN;
-      double testAccuracy = OnlineAccuracyCalculator.Calculate(estimatedTestClassValues, originalTestClassValues, out errorState);
+      double testAccuracy = OnlineAccuracyCalculator.Calculate(originalTestClassValues, estimatedTestClassValues, out errorState);
       if (errorState != OnlineCalculatorError.None) testAccuracy = double.NaN;
 

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs

@@ -108 +108 @@
 
       OnlineCalculatorError errorState;
-      double trainingMSE = OnlineMeanSquaredErrorCalculator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
+      double trainingMSE = OnlineMeanSquaredErrorCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
       TrainingMeanSquaredError = errorState == OnlineCalculatorError.None ? trainingMSE : double.NaN;
-      double testMSE = OnlineMeanSquaredErrorCalculator.Calculate(estimatedTestValues, originalTestValues, out errorState);
+      double testMSE = OnlineMeanSquaredErrorCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);
       TestMeanSquaredError = errorState == OnlineCalculatorError.None ? testMSE : double.NaN;
 
-      double trainingR2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
+      double trainingR2 = OnlinePearsonsRSquaredCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
       TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR2 : double.NaN;
-      double testR2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedTestValues, originalTestValues, out errorState);
+      double testR2 = OnlinePearsonsRSquaredCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);
       TestRSquared = errorState == OnlineCalculatorError.None ? testR2 : double.NaN;