Changeset 4190 for trunk/sources/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression

Timestamp:

08/11/10 11:53:45 (14 years ago)

Author:

gkronber

Message:

Moved upper and lower estimation limit parameters into ISymbolicRegressionEvaluator interface and introduced an Evaluate method in the interface in preparation for a ISymbolicRegressionEvaluator parameter for the validation best solution analyzer. #1117

Location:

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

Files:

• SymbolicRegressionNormalizedMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• SymbolicRegressionScaledNormalizedMeanSquaredErrorEvaluator.cs (modified) (1 diff)

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

@@ -34 +34 @@
   [StorableClass]
   public class SymbolicRegressionNormalizedMeanSquaredErrorEvaluator : SingleObjectiveSymbolicRegressionEvaluator {
-    private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
-    private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
-
-    #region parameter properties
-    public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
-      get { return (IValueLookupParameter<DoubleValue>)Parameters[UpperEstimationLimitParameterName]; }
-    }
-    public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter {
-      get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; }
-    }
-    #endregion
-    #region properties
-    public DoubleValue UpperEstimationLimit {
-      get { return UpperEstimationLimitParameter.ActualValue; }
-    }
-    public DoubleValue LowerEstimationLimit {
-      get { return LowerEstimationLimitParameter.ActualValue; }
-    }
-    #endregion
     public SymbolicRegressionNormalizedMeanSquaredErrorEvaluator()
       : base() {
-      Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
-      Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
     }
 
-    protected override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IEnumerable<int> rows) {
-      double nmse = Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows);
+    public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
+      double nmse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows);
       return nmse;
     }

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

@@ -59 +59 @@
     }
 
-    protected override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IEnumerable<int> rows) {
+    public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
       double alpha, beta;
-      double nmse = Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows, out beta, out alpha);
+      double nmse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, out beta, out alpha);
       AlphaParameter.ActualValue = new DoubleValue(alpha);
       BetaParameter.ActualValue = new DoubleValue(beta);