Changeset 5942 for trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Timestamp:

04/04/11 15:38:16 (14 years ago)

Author:

mkommend

Message:

#1453: Renamed IOnlineEvaluator to IOnlineCalculator

Location:

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

Files:

• ClassificationSolution.cs (modified) (1 diff)
• DiscriminantFunctionClassificationSolution.cs (modified) (1 diff)
• ThresholdCalculators/NormalDistributionCutPointsThresholdCalculator.cs (modified) (1 diff)

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

@@ -85 +85 @@
       IEnumerable<double> originalTestClassValues = ProblemData.Dataset.GetEnumeratedVariableValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
 
-      OnlineEvaluatorError errorState;
-      double trainingAccuracy = OnlineAccuracyEvaluator.Calculate(estimatedTrainingClassValues, originalTrainingClassValues, out errorState);
-      if (errorState != OnlineEvaluatorError.None) trainingAccuracy = double.NaN;
-      double testAccuracy = OnlineAccuracyEvaluator.Calculate(estimatedTestClassValues, originalTestClassValues, out errorState);
-      if (errorState != OnlineEvaluatorError.None) testAccuracy = double.NaN;
+      OnlineCalculatorError errorState;
+      double trainingAccuracy = OnlineAccuracyCalculator.Calculate(estimatedTrainingClassValues, originalTrainingClassValues, out errorState);
+      if (errorState != OnlineCalculatorError.None) trainingAccuracy = double.NaN;
+      double testAccuracy = OnlineAccuracyCalculator.Calculate(estimatedTestClassValues, originalTestClassValues, out errorState);
+      if (errorState != OnlineCalculatorError.None) testAccuracy = double.NaN;
 
       TrainingAccuracy = trainingAccuracy;

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

@@ -105 +105 @@
       IEnumerable<double> originalTestValues = ProblemData.Dataset.GetEnumeratedVariableValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
 
-      OnlineEvaluatorError errorState;
-      double trainingMSE = OnlineMeanSquaredErrorEvaluator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
-      TrainingMeanSquaredError = errorState == OnlineEvaluatorError.None ? trainingMSE : double.NaN;
-      double testMSE = OnlineMeanSquaredErrorEvaluator.Calculate(estimatedTestValues, originalTestValues, out errorState);
-      TestMeanSquaredError = errorState == OnlineEvaluatorError.None ? testMSE : double.NaN;
+      OnlineCalculatorError errorState;
+      double trainingMSE = OnlineMeanSquaredErrorCalculator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
+      TrainingMeanSquaredError = errorState == OnlineCalculatorError.None ? trainingMSE : double.NaN;
+      double testMSE = OnlineMeanSquaredErrorCalculator.Calculate(estimatedTestValues, originalTestValues, out errorState);
+      TestMeanSquaredError = errorState == OnlineCalculatorError.None ? testMSE : double.NaN;
 
-      double trainingR2 = OnlinePearsonsRSquaredEvaluator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
-      TrainingRSquared = errorState == OnlineEvaluatorError.None ? trainingR2 : double.NaN;
-      double testR2 = OnlinePearsonsRSquaredEvaluator.Calculate(estimatedTestValues, originalTestValues, out errorState);
-      TestRSquared = errorState == OnlineEvaluatorError.None ? testR2 : double.NaN;
+      double trainingR2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedTrainingValues, originalTrainingValues, out errorState);
+      TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR2 : double.NaN;
+      double testR2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedTestValues, originalTestValues, out errorState);
+      TestRSquared = errorState == OnlineCalculatorError.None ? testR2 : double.NaN;
     }
 

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators/NormalDistributionCutPointsThresholdCalculator.cs

@@ -64 +64 @@
         double classValue = group.Key;
         double mean, variance;
-        OnlineEvaluatorError meanErrorState, varianceErrorState;
+        OnlineCalculatorError meanErrorState, varianceErrorState;
         OnlineMeanAndVarianceCalculator.Calculate(estimatedClassValues, out mean, out variance, out meanErrorState, out varianceErrorState);
 
-        if (meanErrorState == OnlineEvaluatorError.None && varianceErrorState == OnlineEvaluatorError.None) {
+        if (meanErrorState == OnlineCalculatorError.None && varianceErrorState == OnlineCalculatorError.None) {
           classMean[classValue] = mean;
           classStdDev[classValue] = Math.Sqrt(variance);