Table 3.

Performance analysis of probabilistic features frameworks.

Mode	Classifier	Accuracy	MCC	K	PR	FS	Sn	Sp
48D probabilistic features	EX	0.9703	0.9409	0.9407	0.9820	0.9711	0.9604	0.9810
	RF	0.9624	0.9248	0.9247	0.9709	0.9634	0.9560	0.9692
	KNN	0.9635	0.9278	0.9271	0.9839	0.9641	0.9450	0.9834
	XGB	0.9658	0.9316	0.9316	0.9732	0.9668	0.9604	0.9716
	Voting	0.9624	0.9257	0.9248	0.9839	0.9629	0.9428	0.9834
	AMP-RNNpro	0.9715	0.9431	0.9430	0.9799	0.9723	0.9648	0.9787

Significant values are in bold.