SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

BMC Bioinformatics

Table 4 The AUC, AUPR, Precision, Recall, F1_score and Accuracy of eight computational methods

Methond	AUC	AUPR	Precision	Recall	F1_score	Accuracy
SMALF	0.9503	0.9472	0.8808	0.8931	0.8868	0.8860
GBDT-LR	0.9274	0.9014	0.8315	0.8273	0.8302	0.8304
ABMDA	0.8841	0.8807	0.8152	0.7827	0.7908	0.8027
LMTRDA	0.8479	0.8217	0.8013	0.6190	0.7067	0.7327
ICFMDA	0.8132	0.7913	0.7756	0.7534	0.7643	0.7677
RFMDA	0.7388	0.7034	0.6253	0.9548	0.7453	0.6912
MCMDA	0.7189	0.7061	0.6801	0.6743	0.6771	0.6788
GRMDA	0.6716	0.6403	0.6284	0.6573	0.6425	0.6341

ISSN: 1471-2105