Table 9.

Performance of FCSO, FKH, and FBFO classifiers and super learner on WDBC dataset.

Feature selection algorithm	Size of feature subset	TN	FP	FN	TP	Accuracy	Sensitivity	Specificity	Precision	F-score
CSO	15	137	4	6	165	96.79	96.49	97.16	97.63	0.97
KH	17	139	2	5	166	97.76	97.08	98.58	98.81	0.98
BFO	18	139	2	8	163	96.79	95.32	98.58	98.79	0.97
Super learner	—	22	0	2	39	96.83	95.12	100.00	100.00	0.98