From: Ensemble learning for the early prediction of neonatal jaundice with genetic features
Variables | Method | AUC | F1-score | Precision |
---|---|---|---|---|
CRF | Lightgbm | 0.792 (0.757–0.828) | 0.213 (0.171–0.251) | 0.136 (0.109–0.161) |
 | Cart | 0.553 (0.509–0.592) | 0.150 (0.074–0.211) | 0.137 (0.074–0.191) |
 | Logistic | 0.785 (0.753–0.821) | 0.210 (0.178–0.240) | 0.122 (0.103–0.141) |
 | Naive Bayes | 0.735 (0.673–0.782) | 0.165 (0.129–0.188) | 0.091 (0.069–0.104) |
 | rf | 0.766 (0.711–0.806) | 0.206 (0.177–0.245) | 0.123 (0.106–0.147) |
GV36 | Lightgbm | 0.603 (0.546–0.662) | 0.149 (0.105–0.189) | 0.105 (0.074–0.131) |
 | Cart | 0.558 (0.522–0.598) | 0.149 (0.105–0.191) | 0.110 (0.079–0.139) |
 | Logistic | 0.569 (0.519–0.614) | 0.118 (0.093–0.141) | 0.068 (0.053–0.081) |
 | Naive bays | 0.562 (0.509–0.622) | 0.112 (0.106–0.116) | 0.059 (0.057–0.062) |
 | rf | 0.587 (0.522–0.652) | 0.148 (0.104–0.197) | 0.103 (0.074–0.136) |
CRF_GV36 | Lightgbm | 0.820 (0.785–0.857) | 0.277 (0.218–0.333) | 0.204 (0.160–0.247) |
 | Cart | 0.569 (0.517–0.621) | 0.184 (0.103–0.269) | 0.175 (0.095–0.250) |
 | Logistic | 0.781 (0.730–0.816) | 0.218 (0.185–0.251) | 0.129 (0.110–0.150) |
 | Naive Bayes | 0.642 (0.563–0.707) | 0.114 (0.105–0.124) | 0.061 (0.056–0.067) |
 | rf | 0.792 (0.753–0.833) | 0.228 (0.193–0.259) | 0.139 (0.118–0.158) |