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Table 2 Evaluation of model selection

From: Model selection based on logistic regression in a highly correlated candidate gene region

   Average Prediction Error (SE)a
Selection methods No. selected SNPs Without regularization Ridge penalty Random forests
Stepwise/AIC 9 0.1536 (0.0049) 0.1506 (0.0044) 0.1586 (0.0068)
Lasso/AIC 29 0.1572 (0.0051) 0.1450 (0.0046) 0.1469 (0.0059)
Lasso/CV 17 0.1461 (0.0052) 0.1428 (0.0060) 0.1558 (0.0052)
Bayesian 2 0.1306 (0.0052) b 0.1306 (0.0052) 0.1336 (0.0043)
Trait locus DR/C*   0.1572 (0.0058)  
  1. aAverage prediction error was calculated from Replicates 2 to 10 using the optimally selected set of SNPs from Replicate 1.
  2. bBold indicates the minimum average prediction error.