Multiteam Competitive Optimization Algorithm and Its Application in Bearing Fault Diagnosis

Table 6

The comparison of test sample recognition accuracy for Indian liver patients.

Algorithm	Recognition accuracy 1	Recognition accuracy 2	Recognition accuracy 3
K-MTCO	73.33% (88/120)	74.17% (89/120)	73.33% (88/120)
	(30/60) (58/60)	(30/60) (59/60)	(35/60) (53/60)
S-MTCO	71.67% (86/120)	72.50% (87/120)	72.50% (87/120)
	(35/60) (51/60)	(35/60) (52/60)	(35/60) (52/60)
SVM	43.33% (52/120)	44.17% (53/120)	44.17% (53/120)
	(33/60) (19/60)	(34/60) (19/60)	(34/60) (19/60)
BP	50.83% (61/120)	43.33% (52/120)	55.83% (67/120)
	(28/60) (33/60)	(28/60) (24/60)	(33/60) (34/60)
LVQ	67.50% (81/120)	69.17% (83/120)	59.17% (71/120)
	(43/60) (39/60)	(30/60) (53/60)	(36/60) (35/60)
k-NN	k = 1 : 52.50% (63/120)	k = 34 : 67.50% (81/120)	k = 3 : 47.50% (57/120)
	(29/60) (34/60)	(21/60) (60/60)	(24/60) (33/60)