Changeset 8206 for branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers

Timestamp:

07/03/12 16:46:35 (12 years ago)

Author:

gkronber

Message:

#1847: merged r8084:8205 from trunk into GP move operators branch

Location:

branches/GP-MoveOperators

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisComplexityAnalyzer.cs (deleted)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs (modified) (6 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer.cs (modified) (7 diffs)

branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -26 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Operators;
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using System;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -38 +37 @@
   [Item("SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer", "An operator that analyzes the Pareto-best symbolic data analysis solution for single objective symbolic data analysis problems.")]
   [StorableClass]
-  public abstract class SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer<T> : SymbolicDataAnalysisSingleObjectiveAnalyzer
-    where T : class, ISymbolicDataAnalysisSolution {
+  public abstract class SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer<S, T> : SymbolicDataAnalysisSingleObjectiveAnalyzer, ISymbolicDataAnalysisInterpreterOperator, ISymbolicDataAnalysisBoundedOperator
+    where T : class, ISymbolicDataAnalysisSolution
+    where S : class, IDataAnalysisProblemData {
+    private const string ProblemDataParameterName = "ProblemData";
     private const string TrainingBestSolutionsParameterName = "Best training solutions";
     private const string TrainingBestSolutionQualitiesParameterName = "Best training solution qualities";
     private const string ComplexityParameterName = "Complexity";
+    private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicDataAnalysisTreeInterpreter";
+    private const string EstimationLimitsParameterName = "EstimationLimits";
 
     public override bool EnabledByDefault {
@@ -58 +61 @@
       get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters[ComplexityParameterName]; }
     }
+    public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
+      get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
+    }
+    public ILookupParameter<S> ProblemDataParameter {
+      get { return (ILookupParameter<S>)Parameters[ProblemDataParameterName]; }
+    }
+    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
+      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
+    }
     #endregion
     #region properties
@@ -72 +84 @@
     [StorableConstructor]
     protected SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
-    protected SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer(SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer<T> original, Cloner cloner) : base(original, cloner) { }
+    protected SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer(SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer<S, T> original, Cloner cloner) : base(original, cloner) { }
     public SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer()
       : base() {
+      Parameters.Add(new LookupParameter<S>(ProblemDataParameterName, "The problem data for the symbolic data analysis solution."));
       Parameters.Add(new LookupParameter<ItemList<T>>(TrainingBestSolutionsParameterName, "The training best (Pareto-optimal) symbolic data analysis solutions."));
       Parameters.Add(new LookupParameter<ItemList<DoubleArray>>(TrainingBestSolutionQualitiesParameterName, "The qualities of the training best (Pareto-optimal) solutions."));
       Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>(ComplexityParameterName, "The complexity of each tree."));
+      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The symbolic data analysis tree interpreter for the symbolic expression tree."));
+      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic classification model."));
     }
 
@@ -100 +115 @@
 
       List<double> complexities;
-      if (ComplexityParameter.ActualValue != null) {
+      if (ComplexityParameter.ActualValue != null && ComplexityParameter.ActualValue.Length == qualities.Count) {
         complexities = ComplexityParameter.ActualValue.Select(x => x.Value).ToList();
       } else {

branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -26 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Operators;
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using System;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -38 +37 @@
   [Item("SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer", "An operator that analyzes the Pareto-best symbolic data analysis solution for single objective symbolic data analysis problems.")]
   [StorableClass]
-  public abstract class SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer<S, T, U> : SymbolicDataAnalysisSingleObjectiveValidationAnalyzer<T, U>
+  public abstract class SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer<S, T, U> : SymbolicDataAnalysisSingleObjectiveValidationAnalyzer<T, U>, ISymbolicDataAnalysisBoundedOperator
     where S : class, ISymbolicDataAnalysisSolution
     where T : class, ISymbolicDataAnalysisSingleObjectiveEvaluator<U>
@@ -45 +44 @@
     private const string ValidationBestSolutionQualitiesParameterName = "Best validation solution qualities";
     private const string ComplexityParameterName = "Complexity";
+    private const string EstimationLimitsParameterName = "EstimationLimits";
 
     public override bool EnabledByDefault {
@@ -60 +60 @@
       get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters[ComplexityParameterName]; }
     }
+    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
+      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
+    }
+
     #endregion
     #region properties
@@ -80 +84 @@
       Parameters.Add(new LookupParameter<ItemList<DoubleArray>>(ValidationBestSolutionQualitiesParameterName, "The qualities of the validation best (Pareto-optimal) solutions."));
       Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>(ComplexityParameterName, "The complexity of each tree."));
+      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic classification model."));
     }
 
@@ -137 +142 @@
 
       List<double> complexities;
-      if (ComplexityParameter.ActualValue != null) {
+      if (ComplexityParameter.ActualValue != null && ComplexityParameter.ActualValue.Length == trainingQuality.Length) {
         complexities = ComplexityParameter.ActualValue.Select(x => x.Value).ToList();
       } else {