Table 2.

A comparison of GNCM performance on the test set using different sequence tokenizing and word embedding methods

Sequence tokenizing	Word Embedding	Algorithm	Accuracy	F1	Precision	Recall	Cross-Entropy Loss
BPE	CBOW	GNCM	0.9960	0.9957	0.9947	0.9967	0.0126
	Sg	GNCM	0.9922	0.9922	0.9921	0.9923	0.0328
	CBOW	BiLSTM + SAM	0.9647	0.9647	0.9646	0.9648	0.1054
	Sg	BiLSTM + SAM	0.8686	0.8682	0.8781	0.8708	0.3380
HFkmer	CBOW	GNCM	0.9869	0.9869	0.9873	0.9865	0.0391
	Sg	GNCM	0.8072	0.8012	0.8257	0.7998	0.4263
	CBOW	BiLSTM + SAM	0.9935	0.9934	0.9934	0.9934	0.0140
	Sg	BiLSTM + SAM	0.8170	0.8107	0.8400	0.8090	0.4078