From: A review of deep learning applications for genomic selection
A | Â | Model | Trait | RMSE | Â | Â | |
---|---|---|---|---|---|---|---|
 |  | MLP_20 | Yield | 12.79 |  |  | |
 |  |  | Check yield | 11.38 |  |  | |
 |  |  | Yield difference | 12.4 |  |  | |
 |  | LR | Yield | 21.4 |  |  | |
 |  |  | Check yield | 19.87 |  |  | |
 |  |  | Yield difference | 13.11 |  |  | |
 |  | MLP_1 | Yield | 18.04 |  |  | |
 |  |  | Check yield | 15.18 |  |  | |
 |  |  | Yield difference | 15.19 |  |  | |
 |  | RT | Yield | 15.03 |  |  | |
 |  |  | Check yield | 14.87 |  |  | |
 |  |  | Yield difference | 15.92 |  |  | |
B | Method | Maize | Rice | Sorghum | Soy | Spruce | Switch-grass |
 | rrBLUP | 0.44 | 0.34 | 0.63 | 0.46 | 0.32 | 0.61 |
 | BRR | 0.44 | 0.39 | 0.63 | 0.46 | 0.32 | 0.61 |
 | BayesA | 0.42 | 0.38 | 0.63 | 0.47 | 0.32 | 0.61 |
 | BayesB | 0.43 | 0.38 | 0.63 | 0.46 | 0.32 | 0.61 |
 | BL | 0.44 | 0.39 | 0.62 | 0.46 | 0.32 | 0.61 |
 | SVR_lin | 0.41 | 0.38 | 0.62 | 0.43 | 0.19 | 0.6 |
 | SVR_poly | 0.43 | 0.38 | 0.63 | 0.41 | 0.33 | 0.61 |
 | SVR_rbf | 0.39 | 0.38 | 0.63 | 0.04 | 0.34 | 0.6 |
 | RF | 0.43 | 0.4 | 0.58 | 0.36 | 0.35 | 0.57 |
 | GTB | 0.37 | 0.38 | 0.58 | 0.4 | 0.33 | 0.56 |
 | MLP | 0.17 | 0.08 | 0.45 | 0.44 | 0.28 | 0.45 |