Changeset 14927 for branches/PersistenceReintegration/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs

Timestamp:

05/04/17 17:19:35 (7 years ago)

Author:

gkronber

Message:

#2520: changed all usages of StorableClass to use StorableType with an auto-generated GUID (did not add StorableType to other type definitions yet)

File:

• branches/PersistenceReintegration/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs (modified) (3 diffs)

branches/PersistenceReintegration/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs

@@ -27 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Optimization;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Persistence;
 
 namespace HeuristicLab.Problems.DataAnalysis {
@@ -33 +33 @@
   /// Represents a classification solution that uses a discriminant function and classification thresholds.
   /// </summary>
-  [StorableClass]
+  [StorableType("0cf40763-3f72-49c4-a674-a070aec9d032")]
   [Item("DiscriminantFunctionClassificationSolution", "Represents a classification solution that uses a discriminant function and classification thresholds.")]
   public abstract class DiscriminantFunctionClassificationSolutionBase : ClassificationSolutionBase, IDiscriminantFunctionClassificationSolution {
@@ -106 +106 @@
 
       double trainingR = OnlinePearsonsRCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
-      TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR*trainingR : double.NaN;
+      TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR * trainingR : double.NaN;
       double testR = OnlinePearsonsRCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);
-      TestRSquared = errorState == OnlineCalculatorError.None ? testR*testR : double.NaN;
+      TestRSquared = errorState == OnlineCalculatorError.None ? testR * testR : double.NaN;
 
       double trainingNormalizedGini = NormalizedGiniCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);