Changeset 4190 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionScaledMeanAndVarianceSquaredErrorEvaluator.cs

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

File:

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

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

@@ -102 +102 @@
     }
 
-    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 meanSE, varianceSE;
@@ -109 +109 @@
       double mse;
       if (ApplyScaling.Value) {
-        mse = Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows, out beta, out alpha, out meanSE, out varianceSE, out count, out bias, out variance, out covariance);
+        mse = Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable, rows, out beta, out alpha, out meanSE, out varianceSE, out count, out bias, out variance, out covariance);
         Alpha = new DoubleValue(alpha);
         Beta = new DoubleValue(beta);
       } else {
-        mse = CalculateWithScaling(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows, 1, 0, out meanSE, out varianceSE, out count, out bias, out variance, out covariance);
+        mse = CalculateWithScaling(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable, rows, 1, 0, out meanSE, out varianceSE, out count, out bias, out variance, out covariance);
       }
       QualityVariance = new DoubleValue(varianceSE);