Table 1. Open in new tab The evaluation...

Model	Training data set (no. of training	Accuracy	Precision	Recall	F₁ score	No. of missing
PICS	FAST + HTRU + FALFA (13 632)	0.9357	0.2649	0.9540	0.4146	15
PICS-ResNet	FAST + HTRU + FALFA (13 632)	0.9332	0.2612	0.9816	0.4126	6
H-CCNN	FAST (1835)	0.9634	0.3920	0.9632	0.5572	12
V-CCNN	FAST (1835)	0.9173	0.2227	0.9877	0.3634	4
H-CCNN+V-CCNN	FAST (1835)	0.9476	0.3110	0.9816	0.4723	6

Model	Training data set (no. of training	Accuracy	Precision	Recall	F₁ score	No. of missing
PICS	FAST + HTRU + FALFA (13 632)	0.9357	0.2649	0.9540	0.4146	15
PICS-ResNet	FAST + HTRU + FALFA (13 632)	0.9332	0.2612	0.9816	0.4126	6
H-CCNN	FAST (1835)	0.9634	0.3920	0.9632	0.5572	12
V-CCNN	FAST (1835)	0.9173	0.2227	0.9877	0.3634	4
H-CCNN+V-CCNN	FAST (1835)	0.9476	0.3110	0.9816	0.4723	6

Table 1.

The evaluation results of four classifiers on the FAST data set.

Model	Training data set (no. of training	Accuracy	Precision	Recall	F₁ score	No. of missing
	samples)					pulsars
PICS	FAST + HTRU + FALFA (13 632)	0.9357	0.2649	0.9540	0.4146	15
PICS-ResNet	FAST + HTRU + FALFA (13 632)	0.9332	0.2612	0.9816	0.4126	6
H-CCNN	FAST (1835)	0.9634	0.3920	0.9632	0.5572	12
V-CCNN	FAST (1835)	0.9173	0.2227	0.9877	0.3634	4
H-CCNN+V-CCNN	FAST (1835)	0.9476	0.3110	0.9816	0.4723	6

Model	Training data set (no. of training	Accuracy	Precision	Recall	F₁ score	No. of missing
	samples)					pulsars
PICS	FAST + HTRU + FALFA (13 632)	0.9357	0.2649	0.9540	0.4146	15
PICS-ResNet	FAST + HTRU + FALFA (13 632)	0.9332	0.2612	0.9816	0.4126	6
H-CCNN	FAST (1835)	0.9634	0.3920	0.9632	0.5572	12
V-CCNN	FAST (1835)	0.9173	0.2227	0.9877	0.3634	4
H-CCNN+V-CCNN	FAST (1835)	0.9476	0.3110	0.9816	0.4723	6

Notes. The first two models were trained by Guo et al. (2019). The final model, ‘H-CCNN+V-CCNN’, is the embedding model of H-CCNN and V-CCNN. The boldface digits indicate the best performance.

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