Table 9 Mean and standard error of prediction accuracy and prediction error for various methods using dataset 6.
Methods | Accuracy | MSE | Accuracy SE | MSE SE | Percentage(%) gain in Accuracy | Percentage(%) reduction in MSE |
|---|---|---|---|---|---|---|
LASSO* | 0.45 | 0.07 | 0.10 | 0.02 | NA | NA |
Df-Model | 0.49 | 0.06 | 0.10 | 0.02 | 8.9 | 14.3 |
Df-Regpath | 0.47 | 0.06 | 0.10 | 0.02 | 4.5 | 14.3 |
Df-Cvpath | 0.49 | 0.06 | 0.10 | 0.02 | 8.9 | 14.3 |
Df-Lambda | 0.51 | 0.05 | 0.09 | 0.009 | 13.4 | 28.6 |
Inverse Chi | 0.55 | 0.04 | 0.07 | 0.006 | 22.2 | 42.9 |
Logit | 0.54 | 0.04 | 0.07 | 0.007 | 20 | 42.9 |
Meanp | 0.57 | 0.04 | 0.08 | 0.007 | 26.67 | 42.9 |
Sumz | 0.54 | 0.04 | 0.08 | 0.007 | 20 | 42.9 |
Regression with t-error | 0.44 | 0.22 | 0.10 | 0.10 | 0 | 0 |
RR | 0.52 | 0.04 | 0.08 | 0.01 | 15.5 | 42.9 |
GBLUP | 0.50 | 0.06 | 0.09 | 0.02 | 11 | 14.3 |
Bayesian LASSO | 0.42 | 0.07 | 0.10 | 0.01 | 0 | 0 |
