Changeset 5365 for trunk/sources

Timestamp:

01/24/11 17:12:08 (14 years ago)

Author:

cfischer

Message:

Implemented automatic adaptation of maximization parameter for symbolic regression and classification problems; Added new maximization property in symbolic regression and classification evaluators. #1381

Location:

trunk/sources

Files:

• HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/SymbolicClassificationProblem.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SingleObjectiveSymbolicRegressionEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Interfaces/ISymbolicRegressionEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/SymbolicClassificationProblem.cs

@@ -199 +199 @@
       ParameterizeEvaluator();
       ParameterizeAnalyzers();
+      ParameterizeProblem();
       base.OnEvaluatorChanged();
     }
@@ -340 +341 @@
       }
     }
+
+    private void ParameterizeProblem() {
+      if (Maximization != null) {
+        Maximization.Value = Evaluator.Maximization;
+      } else {
+        Maximization = new BoolValue(Evaluator.Maximization);
+      }
+    }
     #endregion
   }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SingleObjectiveSymbolicRegressionEvaluator.cs

@@ -87 +87 @@
     #endregion
     #region properties
+    public abstract bool Maximization { get; }
+
     public IRandom Random {
       get { return RandomParameter.ActualValue; }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionMeanSquaredErrorEvaluator.cs

@@ -33 +33 @@
   [StorableClass]
   public class SymbolicRegressionMeanSquaredErrorEvaluator : SingleObjectiveSymbolicRegressionEvaluator {
+
+    public override bool Maximization {
+      get { return false; }
+    }
 
     [StorableConstructor]

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs

@@ -33 +33 @@
   [StorableClass]
   public class SymbolicRegressionPearsonsRSquaredEvaluator : SingleObjectiveSymbolicRegressionEvaluator {
+
+    public override bool Maximization {
+      get { return true; }
+    }
+    
     [StorableConstructor]
     protected SymbolicRegressionPearsonsRSquaredEvaluator(bool deserializing) : base(deserializing) { }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Interfaces/ISymbolicRegressionEvaluator.cs

@@ -29 +29 @@
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
   public interface ISymbolicRegressionEvaluator : ISingleObjectiveEvaluator {
+    bool Maximization { get; }
+
     ILookupParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter { get; }
     ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter { get; }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs

@@ -124 +124 @@
       ParameterizeEvaluator();
       ParameterizeAnalyzers();
+      ParameterizeProblem();
       RaiseEvaluatorChanged(e);
     }
@@ -192 +193 @@
       }
     }
+
+    private void ParameterizeProblem() {
+      if (MaximizationParameter.Value != null) {
+        MaximizationParameter.Value.Value = Evaluator.Maximization;
+      } else {
+        MaximizationParameter.Value = new BoolValue(Evaluator.Maximization);
+      }
+    }
     #endregion
   }