Table 2.

Comparison of the prediction performance of the ELMDA framework and a single classifier

Fold	Precision	Recall	F1-score	AUC	AUPR
SVM	0.8369 ± 0.0085	0.8371 ± 0.0143	0.8370 ± 0.0075	0.9091 ± 0.0031	0.9057 ± 0.0036
GBDT	0.8369 ± 0.0107	0.8490 ± 0.0057	0.8429 ± 0.0054	0.9172 ± 0.0034	0.9138 ± 0.0039
RF	0.8424 ± 0.0108	0.8354 ± 0.0131	0.8388 ± 0.0091	0.9141 ± 0.0049	0.9123 ± 0.0047
XGboost	0.8471 ± 0.0090	0.8486 ± 0.0099	0.8478 ± 0.0076	0.9191 ± 0.0039	0.9165 ± 0.0045
ELMDA	0.8485 ± 0.0139	0.8536 ± 0.0101	0.8510 ± 0.0094	0.9229 ± 0.0035	0.9217 ± 0.0031