From: A review of deep learning applications for genomic selection
A | Model | Trait | RMSE | ||||
---|---|---|---|---|---|---|---|
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 |