Changeset 15910 for branches/2886_SymRegGrammarEnumeration/HeuristicLab.Algorithms.DataAnalysis.SymRegGrammarEnumeration/Analysis/RSquaredEvaluator.cs

Timestamp:

04/17/18 16:59:57 (6 years ago)

Author:

lkammere

Message:

#2886: Fix length parameter when priorizing phrases and add weighting parameter to control exploration/exploitation during search, fix copy constructors in Analyzers

File:

• branches/2886_SymRegGrammarEnumeration/HeuristicLab.Algorithms.DataAnalysis.SymRegGrammarEnumeration/Analysis/RSquaredEvaluator.cs (modified) (4 diffs)

branches/2886_SymRegGrammarEnumeration/HeuristicLab.Algorithms.DataAnalysis.SymRegGrammarEnumeration/Analysis/RSquaredEvaluator.cs

@@ -23 +23 @@
     public RSquaredEvaluator() { }
 
-    protected RSquaredEvaluator(RSquaredEvaluator original, Cloner cloner) {
+    protected RSquaredEvaluator(RSquaredEvaluator original, Cloner cloner) : base(original, cloner) {
       this.OptimizeConstants = original.OptimizeConstants;
     }
@@ -52 +52 @@
     private void OnStarted(object sender, EventArgs eventArgs) {
       GrammarEnumerationAlgorithm algorithm = (GrammarEnumerationAlgorithm)sender;
-      algorithm.Results.Add(new Result(BestTrainingQualityResultName, new DoubleValue(-1.0)));
 
       algorithm.BestTrainingSentence = null;
@@ -75 +74 @@
       double r2 = Evaluate(problemData, tree, OptimizeConstants);
 
-      var bestR2Result = (DoubleValue)algorithm.Results[BestTrainingQualityResultName].Value;
-      bool better = r2 > bestR2Result.Value;
-      bool equallyGood = r2.IsAlmost(bestR2Result.Value);
+      double bestR2 = 0.0;
+      if (algorithm.Results.ContainsKey(BestTrainingQualityResultName))
+        bestR2 = ((DoubleValue)algorithm.Results[BestTrainingQualityResultName].Value).Value;
+      bool better = r2 > bestR2;
+      bool equallyGood = r2.IsAlmost(bestR2);
       bool shorter = false;
 
@@ -85 +86 @@
       }
       if (better || (equallyGood && shorter)) {
-        bestR2Result.Value = r2;
+        algorithm.Results.AddOrUpdateResult(BestTrainingQualityResultName, new DoubleValue(r2));
 
         SymbolicRegressionModel model = new SymbolicRegressionModel(