Changeset 5759 for branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

Timestamp:

03/19/11 02:22:45 (13 years ago)

Author:

mkommend

Message:

#1418:

• Worked on IntRange and DoubleRange
• Updated evaluators, analyzers, problems and problem data to use IntRanges
• Removed properties to access the value of LookupParameter
• Corrected files.txt

File:

• branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs (modified) (3 diffs)

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

@@ -31 +31 @@
   [StorableClass]
   [Creatable("Problems")]
-  public class SymbolicRegressionSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IRegressionProblemData, ISymbolicRegressionSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>,IRegressionProblem {
+  public class SymbolicRegressionSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IRegressionProblemData, ISymbolicRegressionSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IRegressionProblem {
     private const double PunishmentFactor = 10;
     private const int InitialMaximumTreeDepth = 8;
@@ -72 +72 @@
       InitializeOperators();
       UpdateEstimationLimits();
-      UpdateDatasetPartitions();
     }
 
@@ -83 +82 @@
 
     private void UpdateEstimationLimits() {
-      if (ProblemData.TrainingPartitionStart.Value < ProblemData.TrainingPartitionEnd.Value) {
-        var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartitionStart.Value, ProblemData.TrainingPartitionEnd.Value);
+      if (ProblemData.TrainingPartition.Start < ProblemData.TrainingPartition.End) {
+        var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartition.Start, ProblemData.TrainingPartition.End);
         var mean = targetValues.Average();
         var range = targetValues.Max() - targetValues.Min();