Changeset 4194 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicVectorRegressionScaledNormalizedMseEvaluator.cs

Timestamp:

08/11/10 13:00:53 (14 years ago)

Author:

gkronber

Message:

Created a feature/exploration branch for new data analysis features #1142

Location:

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression

Files:

• . (copied) (copied from trunk/sources/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression)
• 3.3/Symbolic/Evaluators/SymbolicVectorRegressionScaledNormalizedMseEvaluator.cs (modified) (3 diffs)

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

@@ -34 +34 @@
   [Item("SymbolicVectorRegressionScaledNormalizedMseEvaluator", "Represents an operator that calculates the sum of the normalized mean squared error over all components.")]
   [StorableClass]
-  public class SymbolicVectorRegressionScaledNormalizedMseEvaluator : SymbolicVectorRegressionEvaluator, ISingleObjectiveSymbolicVectorRegressionEvaluator {
-    private const string QualityParameterName = "ScaledNormalizedMeanSquaredError";
+  public class SymbolicVectorRegressionScaledNormalizedMseEvaluator : SingleObjectiveSymbolicVectorRegressionEvaluator {
     private const string AlphaParameterName = "Alpha";
     private const string BetaParameterName = "Beta";
 
     #region parameter properties
-    public ILookupParameter<DoubleValue> QualityParameter {
-      get { return (ILookupParameter<DoubleValue>)Parameters[QualityParameterName]; }
-    }
     public ILookupParameter<DoubleArray> AlphaParameter {
       get { return (ILookupParameter<DoubleArray>)Parameters[AlphaParameterName]; }
@@ -54 +50 @@
     public SymbolicVectorRegressionScaledNormalizedMseEvaluator()
       : base() {
-      Parameters.Add(new LookupParameter<DoubleValue>(QualityParameterName, "The sum of the normalized mean squared error over all components of the symbolic vector regression solution encoded as a symbolic expression tree."));
       Parameters.Add(new LookupParameter<DoubleArray>(AlphaParameterName, "The alpha parameter for linear scaling."));
       Parameters.Add(new LookupParameter<DoubleArray>(BetaParameterName, "The beta parameter for linear scaling."));
     }
 
-    public override void Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) {
+    public override double Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) {
       List<string> targetVariablesList = targetVariables.ToList();
       double nmseSum = 0.0;
@@ -87 +82 @@
       AlphaParameter.ActualValue = alpha;
       BetaParameter.ActualValue = beta;
-      QualityParameter.ActualValue = new DoubleValue(nmseSum);
+      return nmseSum;
     }
   }