Changeset 4022 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic

Timestamp:

07/09/10 17:01:36 (14 years ago)

Author:

gkronber

Message:

Worked on symbolic regression classes to prepare for time series prognosis plugin. #1081

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs

@@ -246 +246 @@
 
       #region validation best model
-      int targetVariableIndex = ProblemData.Dataset.GetVariableIndex(ProblemData.TargetVariable.Value);
+      string targetVariable = ProblemData.TargetVariable.Value;
       int validationStart = ValidiationSamplesStart.Value;
       int validationEnd = ValidationSamplesEnd.Value;
@@ -257 +257 @@
       OnlineMeanSquaredErrorEvaluator mseEvaluator = new OnlineMeanSquaredErrorEvaluator();
       foreach (var scaledTree in scaledTrees) {
-        mseEvaluator.Reset();
-        IEnumerable<double> estimatedValidationValues = SymbolicExpressionTreeInterpreter.GetSymbolicExpressionTreeValues(scaledTree, ProblemData.Dataset, Enumerable.Range(validationStart, validationEnd - validationStart));
-        IEnumerable<double> originalValidationValues = ProblemData.Dataset.GetEnumeratedVariableValues(targetVariableIndex, validationStart, validationEnd);
-        var estimatedEnumerator = estimatedValidationValues.GetEnumerator();
-        var originalEnumerator = originalValidationValues.GetEnumerator();
-        while (estimatedEnumerator.MoveNext() & originalEnumerator.MoveNext()) {
-          double estimated = estimatedEnumerator.Current;
-          if (double.IsNaN(estimated)) estimated = upperEstimationLimit;
-          else estimated = Math.Min(upperEstimationLimit, Math.Max(lowerEstimationLimit, estimated));
-          mseEvaluator.Add(originalEnumerator.Current, estimated);
-        }
-        double validationMse = mseEvaluator.MeanSquaredError;
+        double validationMse = SymbolicRegressionMeanSquaredErrorEvaluator.Calculate(SymbolicExpressionTreeInterpreter, scaledTree,
+          lowerEstimationLimit, upperEstimationLimit,
+          ProblemData.Dataset, targetVariable,
+          validationStart, validationEnd);
+
         if (validationMse < bestValidationMse) {
           bestValidationMse = validationMse;