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Table 3 Accuracies and unbiasedness of genomic prediction on TNB and NBA from seven methods in 20 replicates of 5-fold CV

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
  1. 1 TNB: total number of piglets born
  2. 2 NBA: number of piglets born alive
  3. 3 Accuracy: the correlation between corrected phenotypes and predicted values of the validation population;
  4. 4 Unbiasedness: the regression of corrected phenotypes onto the predicted values
  5. The different superscript of accuracy indicates the significant difference by the Hotelling-Williams test