Table 6 Mean and standard error of prediction accuracy and prediction error for various methods using dataset 3.
Methods | Accuracy | MSE | Accuracy SE | MSE SE | Percentage(%) gain in Accuracy | Percentage(%) reduction in MSE |
|---|---|---|---|---|---|---|
LASSO* | 0.52 | 13.3 | 0.1 | 2.7 | NA | NA |
Df-Model | 0.60 | 9.5 | 0.09 | 2.2 | 15.4 | 28.6 |
Df-Regpath | 0.57 | 10.8 | 0.08 | 1.9 | 9.6 | 18.8 |
Df-Cvpath | 0.60 | 9.4 | 0.08 | 2.1 | 15.4 | 29.3 |
Df-Lambda | 0.58 | 10.7 | 0.08 | 2.2 | 11.5 | 19.5 |
Inverse Chi | 0.68 | 7.2 | 0.08 | 1.4 | 30.8 | 45.8 |
Logit | 0.67 | 7.5 | 0.08 | 1.5 | 28.8 | 43.6 |
Meanp | 0.66 | 7.9 | 0.08 | 1.5 | 26.9 | 40.6 |
Sumz | 0.68 | 7.3 | 0.07 | 1.6 | 30.8 | 45.1 |
Regression with t-error | 0.61 | 7.4 | 0.08 | 1.8 | 17.3 | 44.4 |
RR | 0.68 | 7.5 | 0.07 | 1.3 | 30.8 | 43.6 |
GBLUP | 0.65 | 7.5 | 0.07 | 1.5 | 25 | 43.6 |
Bayesian LASSO | 0.62 | 8.9 | 0.8 | 1.6 | 19.2 | 33.1 |
