Table 2.

(a) Performance scores of our proposed model with graphlet feature, sequence-based feature, and ensemble feature on HIPPIE dataset³¹; (b) performance scores of our proposed model with graphlet feature, sequence-based feature, and ensemble feature on MPXV-Human dataset³².

Features and dataset	Parameters	Graphlet feature	Sequence-based feature	Ensemble feature
(a)
Graphlet feature, sequence-based feature, and ensemble feature (HIPPIE19)	Precision	0.9047	0.8431	0.8647
	Recall	0.5735	0.7345	0.7622
	MCC score	0.5514	0.6028	0.6476
	F1-score	0.702	0.7851	0.8103
	AUC–ROC score	0.7566	0.7989	0.8215
	AUPRC score	0.7321	0.7520	0.7780
(b)
Graphlet feature, sequence-based feature, and ensemble feature (MPXV-Human20)	Precision	0.6165	0.8053	0.8848
	Recall	0.1822	0.8391	0.9484
	MCC score	0.097	0.6368	0.8271
	F1-score	0.2812	0.8219	0.9155
	AUPRC score	0.5212	0.7562	0.8649

The best values are in bold.