Changeset 18103 for branches/3136_Structural_GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredTreeComplexityEvaluator.cs

Timestamp:

12/02/21 17:23:10 (2 years ago)

Author:

dpiringe

Message:

#3136

• refactor the evaluation logic of NMSESingleObjectiveConstraintsEvaluator
• refactor the new method Evaluate for PearsonRSquaredAverageSimilarityEvaluator
• change the parameter order of some evaluate/calculate methods

File:

• branches/3136_Structural_GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredTreeComplexityEvaluator.cs (modified) (1 diff)

branches/3136_Structural_GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredTreeComplexityEvaluator.cs

@@ -61 +61 @@
     }
 
-    public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling, int decimalPlaces) {
-      double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, problemData, rows, applyLinearScaling);
+    public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree tree, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling, int decimalPlaces) {
+      double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(
+         tree, problemData, rows, 
+         interpreter, applyLinearScaling, 
+         lowerEstimationLimit, upperEstimationLimit);
       if (decimalPlaces >= 0)
         r2 = Math.Round(r2, decimalPlaces);
-      return new double[2] { r2, SymbolicDataAnalysisModelComplexityCalculator.CalculateComplexity(solution) };
+      return new double[2] { r2, SymbolicDataAnalysisModelComplexityCalculator.CalculateComplexity(tree) };
     }