Changeset 4112 for trunk/sources/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators

Timestamp:

07/27/10 14:36:27 (14 years ago)

Author:

gkronber

Message:

Fixed some bugs in multi-variate regression classes. #1089

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators

Files:

• SymbolicRegressionNormalizedMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• SymbolicVectorRegressionNormalizedMseEvaluator.cs (modified) (1 diff)
• SymbolicVectorRegressionScaledMseEvaluator.cs (modified) (1 diff)
• SymbolicVectorRegressionScaledNormalizedMseEvaluator.cs (modified) (1 diff)

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

@@ -65 +65 @@
 
     public static double Calculate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
-      int targetVariableIndex = dataset.GetVariableIndex(targetVariable);
-      var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, dataset, rows);
-      var originalValues = dataset.GetEnumeratedVariableValues(targetVariableIndex, rows);
-      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
-      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
-      OnlineNormalizedMeanSquaredErrorEvaluator mseEvaluator = new OnlineNormalizedMeanSquaredErrorEvaluator();
-
-      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
-        double estimated = estimatedEnumerator.Current;
-        double original = originalEnumerator.Current;
-        if (double.IsNaN(estimated))
-          estimated = upperEstimationLimit;
-        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.NormalizedMeanSquaredError;
-      }
+      return SymbolicRegressionScaledNormalizedMeanSquaredErrorEvaluator.CalculateWithScaling(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, 1.0, 0.0);
     }
   }

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

@@ -73 +73 @@
         tree.Root.SubTrees[0].AddSubTree(treeNode);
       }
-      return nmseSum / targetVariablesList.Count;
+      return nmseSum;
     }
   }

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

@@ -75 +75 @@
         double mse = SymbolicRegressionScaledMeanSquaredErrorEvaluator.Calculate(interpreter, tree,
           lowerEstimationBound[i], upperEstimationBound[i],
-          problemData.Dataset, targetVariablesList[i], rows, out compAlpha, out compBeta);
+          problemData.Dataset, targetVariablesList[i], rows, out compBeta, out compAlpha);
 
         qualities[i] = mse;

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

@@ -87 +87 @@
       AlphaParameter.ActualValue = alpha;
       BetaParameter.ActualValue = beta;
-      QualityParameter.ActualValue = new DoubleValue(nmseSum / targetVariables.Count());
+      QualityParameter.ActualValue = new DoubleValue(nmseSum);
     }
   }