Changeset 4391 for branches/HeuristicLab.Classification/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/Evaluators

Timestamp:

09/14/10 18:46:12 (14 years ago)

Author:

mkommend

Message:

updated classification branch (ticket #939)

Location:

branches/HeuristicLab.Classification/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/Evaluators

Files:

• . (added)
• SymbolicClassificationMeanSquaredErrorEvaluator.cs (moved) (moved from branches/HeuristicLab.Classification/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/SymbolicClassificationMeanSquaredErrorEvaluator.cs) (1 diff)

branches/HeuristicLab.Classification/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/Evaluators/SymbolicClassificationMeanSquaredErrorEvaluator.cs

@@ -20 +20 @@
 #endregion
 
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using HeuristicLab.Problems.DataAnalysis.Evaluators;
-using HeuristicLab.Problems.DataAnalysis.Symbolic;
+using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic;
 
 namespace HeuristicLab.Problems.DataAnalysis.Classification {
   [Item("SymbolicClassificationMeanSquaredErrorEvaluator", "Calculates the mean squared error of a symbolic classification solution.")]
   [StorableClass]
-  public class SymbolicClassifacitionMeanSquaredErrorEvaluator : SingleObjectiveSymbolicClassificationEvaluator {
+  public class SymbolicClassifacitionMeanSquaredErrorEvaluator : SymbolicRegressionMeanSquaredErrorEvaluator, ISymbolicClassificationEvaluator {
+    public ClassificationProblemData ClassificationProblemData {
+      get { return (ClassificationProblemData)RegressionProblemData; }
+    }
 
     public SymbolicClassifacitionMeanSquaredErrorEvaluator()
       : base() {
     }
-
-    public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<double> sortedClassValues, IEnumerable<int> rows) {
-      double mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, sortedClassValues, rows);
-      return mse;
-    }
-
-    public static double Calculate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<double> sortedClassValues, IEnumerable<int> rows) {
-      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, dataset, rows);
-      IEnumerable<double> originalValues = dataset.GetEnumeratedVariableValues(targetVariable, rows);
-      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
-      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
-      OnlineMeanSquaredErrorEvaluator mseEvaluator = new OnlineMeanSquaredErrorEvaluator();
-
-
-      double firstClassValue = sortedClassValues.First();
-      double lastClassValue = sortedClassValues.Last();
-      while (originalEnumerator.MoveNext() && estimatedEnumerator.MoveNext()) {
-        double estimated = estimatedEnumerator.Current;
-        double original = originalEnumerator.Current;
-        if (double.IsNaN(estimated))
-          estimated = upperEstimationLimit;
-        else if (estimated < original && original.IsAlmost(firstClassValue))
-          estimated = original;
-        else if (estimated > original && original.IsAlmost(lastClassValue))
-          estimated = original;
-        else
-          estimated = Math.Min(upperEstimationLimit, Math.Max(lowerEstimationLimit, estimated));
-        mseEvaluator.Add(original, estimated);
-      }
-
-      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
-        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
-      } else {
-        return mseEvaluator.MeanSquaredError;
-      }
-    }
   }
 }