- Timestamp:
- 12/23/10 11:37:29 (14 years ago)
- Location:
- trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators
- Files:
-
- 2 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionScaledMeanAndVarianceSquaredErrorEvaluator.cs
r4722 r5169 115 115 double bias, variance, covariance; 116 116 double mse; 117 if (ApplyScaling.Value) { 118 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); 119 Alpha = new DoubleValue(alpha); 120 Beta = new DoubleValue(beta); 117 if (ExecutionContext != null) { 118 if (ApplyScaling.Value) { 119 mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, out beta, out alpha, out meanSE, out varianceSE, out count, out bias, out variance, out covariance); 120 Alpha = new DoubleValue(alpha); 121 Beta = new DoubleValue(beta); 122 } else { 123 mse = CalculateWithScaling(interpreter, solution,lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, 1, 0, out meanSE, out varianceSE, out count, out bias, out variance, out covariance); 124 } 125 QualityVariance = new DoubleValue(varianceSE); 126 QualitySamples = new IntValue(count); 127 DecompositionBiasParameter.ActualValue = new DoubleValue(bias / meanSE); 128 DecompositionVarianceParameter.ActualValue = new DoubleValue(variance / meanSE); 129 DecompositionCovarianceParameter.ActualValue = new DoubleValue(covariance / meanSE); 121 130 } else { 122 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); 123 } 124 QualityVariance = new DoubleValue(varianceSE); 125 QualitySamples = new IntValue(count); 126 DecompositionBiasParameter.ActualValue = new DoubleValue(bias / meanSE); 127 DecompositionVarianceParameter.ActualValue = new DoubleValue(variance / meanSE); 128 DecompositionCovarianceParameter.ActualValue = new DoubleValue(covariance / meanSE); 131 if (ApplyScalingParameter.Value != null && ApplyScalingParameter.Value.Value) 132 mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, out beta, out alpha, out meanSE, out varianceSE, out count, out bias, out variance, out covariance); 133 else 134 mse = CalculateWithScaling(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, 1, 0, out meanSE, out varianceSE, out count, out bias, out variance, out covariance); 135 } 136 129 137 return mse; 130 138 } -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionScaledMeanSquaredErrorEvaluator.cs
r4722 r5169 70 70 double alpha, beta; 71 71 double mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows, out beta, out alpha); 72 AlphaParameter.ActualValue = new DoubleValue(alpha); 73 BetaParameter.ActualValue = new DoubleValue(beta); 72 if (ExecutionContext != null) { 73 AlphaParameter.ActualValue = new DoubleValue(alpha); 74 BetaParameter.ActualValue = new DoubleValue(beta); 75 } 74 76 return mse; 75 77 }
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