From: Using machine learning to improve the accuracy of genomic prediction of reproduction traits in pigs
Hyper-parameters | Method | TNB1 | NBA2 | ||
---|---|---|---|---|---|
Accuracy3 | Unbiasedness4 | Accuracy3 | Unbiasedness4 | ||
 | GBLUP | 0.248a ± 0.026 | 0.958 ± 0.132 | 0.208a ± 0.025 | 0.931 ± 0.142 |
 | ssGBLUP | 0.251a ± 0.026 | 0.901 ± 0.121 | 0.221ab ± 0.026 | 0.844 ± 0.113 |
 | BayesHE | 0.243a ± 0.025 | 1.015 ± 0.148 | 0.207a ± 0.026 | 1.009 ± 0.171 |
Tuning | SVR | 0.295b ± 0.025 | 1.23 ± 0.119 | 0.254b ± 0.023 | 1.106 ± 0.11 |
KRR | 0.295b ± 0.025 | 1.266 ± 0.125 | 0.256b ± 0.023 | 1.151 ± 0.113 | |
RF | 0.270ab ± 0.029 | 1.229 ± 0.152 | 0.248ab ± 0.028 | 1.188 ± 0.147 | |
Adaboost.R2_SVR | 0.293b ± 0.025 | 1.363 ± 0.138 | 0.254b ± 0.024 | 1.256 ± 0.131 | |
Adaboost.R2_KRR | 0.292b ± 0.025 | 1.344 ± 0.136 | 0.258b ± 0.024 | 1.249 ± 0.129 | |
Default | SVR | 0.255 ± 0.027 | 1.275 ± 0.147 | 0.224 ± 0.023 | 1.098 ± 0.126 |
KRR | 0.264 ± 0.025 | 1.007 ± 0.108 | 0.222 ± 0.024 | 0.879 ± 0.101 | |
RF | 0.246 ± 0.028 | 1.064 ± 0.142 | 0.225 ± 0.027 | 1.002 ± 0.128 | |
Adaboost.R2_SVR | 0.273 ± 0.024 | 0.998 ± 0.106 | 0.228 ± 0.026 | 0.822 ± 0.099 | |
Adaboost.R2_KRR | 0.254 ± 0.024 | 0.759 ± 0.085 | 0.209 ± 0.027 | 0.636 ± 0.085 |