Table 2. Performance of CNN, LSTM and RF models for binary classification using different statistical measures.

Methods	Yeast				Arabidopsis thaliana				Human
	Acc	Sn	Sp	MCC	Acc	Sn	Sp	MCC	Acc	Sn	Sp	MCC
	2-mer
CNN	0.96	0.98	0.93	0.89	0.98	0.97	0.99	0.95	0.99	0.99	0.99	0.99
LSTM	0.64	0.56	0.71	0.27	0.50	0.50	0.50	0.01	0.70	0.69	0.74	0.49
RF	0.87	0.84	0.90	0.74	0.73	0.76	0.70	0.46	0.72	0.76	0.68	0.45
	4-mer
CNN	0.97	0.99	0.95	0.91	0.99	1.00	0.99	0.98	0.99	1.00	0.99	0.99
LSTM	0.86	0.91	0.82	0.73	0.88	0.88	0.90	0.78	0.93	0.94	0.95	0.89
RF	0.81	0.74	0.88	0.62	0.79	0.80	0.79	0.59	0.79	0.80	0.80	0.54
	8-mer
CNN	0.95	0.95	0.96	0.91	0.99	0.99	0.99	0.98	0.98	0.99	0.98	0.98
LSTM	0.79	0.82	0.77	0.58	0.98	0.97	0.98	0.97	0.99	0.99	0.99	0.98
RF	0.73	0.66	0.81	0.47	0.85	0.82	0.88	0.69	0.84	0.81	0.87	0.69