Table 4: The confusion matrix for the Gaussian mixture method using 14variability classes and 28 classification attributes. The last but one line lists the total number of light curves (TOT) to define every class. The last line lists the correct classification rate (CC) for every class separately. The average correct classification rate is about .

	MIRA	SR	CLCEP	DMCEP	RRAB	RRC	RRD	DSCUT	BCEP	SPB	GDOR	EA	EB	EW
MIRA	140	0	3	0	0	0	0	0	0	0	0	0	0	0
SR	0	36	0	0	0	0	0	1	0	0	0	0	0	0
CLCEP	4	1	187	0	0	0	0	0	0	0	0	0	0	0
DMCEP	0	0	0	95	0	0	0	0	0	0	0	0	0	0
RRAB	0	0	2	0	124	0	0	2	0	0	0	0	0	0
RRC	0	0	0	0	0	29	0	4	0	0	0	0	0	0
RRD	0	0	0	0	0	0	57	0	0	0	0	0	0	0
DSCUT	0	5	3	0	5	0	0	90	0	0	0	0	0	0
BCEP	0	0	0	0	0	0	0	30	57	0	0	0	0	0
SPB	0	0	0	0	0	0	0	0	0	47	0	0	0	0
GDOR	0	0	0	0	0	0	0	11	1	0	35	0	0	0
EA	0	0	0	0	0	0	0	1	0	0	0	161	17	0
EB	0	0	0	0	0	0	0	0	0	0	0	5	121	0
EW	0	0	0	0	0	0	0	0	0	0	0	3	9	59
TOT	144	42	195	95	129	29	57	139	58	47	35	169	147	59
CC(%)	97	86	96	100	96	100	100	65	98	100	100	95	82	100