Changeset 4297 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs

Timestamp:

08/23/10 18:54:35 (14 years ago)

Author:

gkronber

Message:

Added output parameter for validation quality to validation analyzer, added input parameter for validation quality to overfitting analyzer, and fixed bugs in pruning operator. #1142

File:

• branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs (modified) (6 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs

@@ -146 +146 @@
       get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
     }
+    public ScopeTreeLookupParameter<DoubleValue> ValidationQualityParameter {
+      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["ValidationQuality"]; }
+    }
 
     public ILookupParameter<IntValue> GenerationsParameter {
@@ -237 +240 @@
       Parameters.Add(new LookupParameter<SymbolicRegressionSolution>("BestTrainingSolution"));
       Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality"));
+      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("ValidationQuality"));
       Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "The number of generations calculated so far."));
       Parameters.Add(new LookupParameter<DoubleValue>(BestSolutionQualityParameterName, "The quality of the best symbolic regression solution."));
@@ -267 +271 @@
         Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality"));
       }
+      if (!Parameters.ContainsKey("ValidationQuality")) {
+        Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("ValidationQuality"));
+      }
       #endregion
     }
@@ -291 +298 @@
       SymbolicExpressionTree bestTrainingTree = trees[0];
       double bestTrainingQuality = qualities[0].Value;
+      ItemArray<DoubleValue> validationQualites = new ItemArray<DoubleValue>(qualities.Length);
       for (int i = 0; i < trees.Length; i++) {
         SymbolicExpressionTree tree = trees[i];
@@ -297 +305 @@
           ProblemData.Dataset, targetVariable,
          rows);
-
+        validationQualites[i] = new DoubleValue(quality);
         if ((Maximization.Value && quality > bestQuality) ||
             (!Maximization.Value && quality < bestQuality)) {
@@ -309 +317 @@
         }
       }
+      ValidationQualityParameter.ActualValue = validationQualites;
 
       var scaledBestTrainingTree = GetScaledTree(bestTrainingTree);