RLFDDA: a meta-path based graph representation learning model for drug–disease association prediction

BMC Bioinformatics

Table 7 Experimental results of different classifiers on B-dataset

Classifier	Acc.	AUC.	Prec.	Recall	s F1-score
AdaBoost	0.6871 ± 0.0073	0.7537 ± 0.0081	0.6825 ± 0.0070	0.6995 ± 0.0121	0.6909 ± 0.0081
GNB	0.6814 ± 0.0067	0.7446 ± 0.0059	0.6774 ± 0.0062	0.6927 ± 0.0111	0.6849 ± 0.0077
KNN	0.7230 ± 0.0036	0.8443 ± 0.0064	0.6538 ± 0.0028	0.9480 ± 0.0052	0.7739 ± 0.0029
LR	0.6705 ± 0.0070	0.7360 ± 0.0082	0.6689 ± 0.0072	0.6752 ± 0.0095	0.6721 ± 0.0074
RF	0.7907 ± 0.0061	0.8728 ± 0.0063	0.7821 ± 0.0084	0.8060 ± 0.0078	0.7938 ± 0.0057

ISSN: 1471-2105