Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs

Timestamp:

01/11/11 15:03:46 (13 years ago)

Author:

gkronber

Message:

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File:

• branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs (modified) (3 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs

@@ -22 +22 @@
 using System;
 using System.Collections.Generic;
+using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Problems.DataAnalysis.Evaluators;
@@ -34 +33 @@
   [StorableClass]
   public class SymbolicRegressionPearsonsRSquaredEvaluator : SingleObjectiveSymbolicRegressionEvaluator {
-    public SymbolicRegressionPearsonsRSquaredEvaluator()
-      : base() {
+    [StorableConstructor]
+    protected SymbolicRegressionPearsonsRSquaredEvaluator(bool deserializing) : base(deserializing) { }
+    protected SymbolicRegressionPearsonsRSquaredEvaluator(SymbolicRegressionPearsonsRSquaredEvaluator original, Cloner cloner)
+      : base(original, cloner) {
     }
+    public SymbolicRegressionPearsonsRSquaredEvaluator() : base() { }
 
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicRegressionPearsonsRSquaredEvaluator(this, cloner);
+    }
     public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
-      double r2 = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows);
-      return r2;
+      double mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows);
+      return mse;
     }
 
@@ -54 +59 @@
         double original = originalEnumerator.Current;
         if (double.IsNaN(estimated))
-          return 0.0;
+          estimated = upperEstimationLimit;
         else
           estimated = Math.Min(upperEstimationLimit, Math.Max(lowerEstimationLimit, estimated));