Changeset 5823

Timestamp:

03/24/11 13:24:09 (13 years ago)

Author:

gkronber

Message:

#1418 fixed minor issues in symbolic data analysis classes.

Location:

trunk/sources

Files:

• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveOverfittingAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveOverfittingAnalyzer.cs

@@ -85 +85 @@
                                     select EvaluatorParameter.ActualValue.Evaluate(childContext, tree, ProblemDataParameter.ActualValue, rows))
                                    .ToArray();
-      double r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      double r = 0.0;
+      try {
+        r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      }
+      catch (alglib.alglibexception) {
+        r = 0.0;
+      }
 
       TrainingValidationQualityCorrelationParameter.ActualValue = new DoubleValue(r);
-
       if (TrainingValidationQualityCorrelationTableParameter.ActualValue == null) {
         var dataTable = new DataTable(TrainingValidationQualityCorrelationTableParameter.Name, TrainingValidationQualityCorrelationTableParameter.Description);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs

@@ -59 +59 @@
       }
       catch (ArgumentException) {
-        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness valuse
+        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness value
         return 0.0;
       }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs

@@ -85 +85 @@
                                     select EvaluatorParameter.ActualValue.Evaluate(childContext, tree, ProblemDataParameter.ActualValue, rows))
                                    .ToArray();
-      double r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      double r = 0.0;
+      try {
+        r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      }
+      catch (alglib.alglibexception) {
+        r = 0.0;
+      }
 
       TrainingValidationQualityCorrelationParameter.ActualValue = new DoubleValue(r);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs

@@ -59 +59 @@
       }
       catch (ArgumentException) {
-        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness valuse
+        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness value
         return 0.0;
       }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs

@@ -93 +93 @@
       int samplesStart = EvaluationPartitionParameter.ActualValue.Start;
       int samplesEnd = EvaluationPartitionParameter.ActualValue.End;
+      int testPartitionStart = ProblemDataParameter.ActualValue.TestPartition.Start;
+      int testPartitionEnd = ProblemDataParameter.ActualValue.TestPartition.End;
 
       if (samplesEnd < samplesStart) throw new ArgumentException("Start value is larger than end value.");
@@ -98 +100 @@
       if (count == 0) count = 1;
       return RandomEnumerable.SampleRandomNumbers(seed, samplesStart, samplesEnd, count)
-        .Where(i => i < ProblemDataParameter.ActualValue.TestPartition.Start || ProblemDataParameter.ActualValue.TestPartition.End <= i);
+        .Where(i => i < testPartitionStart || testPartitionEnd <= i);
     }
   }