Table 3.

The confusion matrix of Bayesian network classification. Each row of the matrix represents the instances in a predicted cluster, and each column represents the instances in an actual cluster. C1–C9 are the logograms for clusters 1–9

	C1	C2	C3	C4	C5	C6	C7	C8	C9
C1	52	0	0	0	2	0	0	0	0
C2	2	51	0	0	0	0	0	1	0
C3	0	0	26	3	3	0	1	1	0
C4	0	0	0	33	0	0	1	0	1
C5	2	4	2	0	78	0	0	2	0
C6	1	1	0	0	0	17	0	0	0
C7	0	0	0	0	0	0	13	1	0
C8	0	0	0	0	0	1	0	24	0
C9	0	0	0	0	0	0	0	1	8

The bold text in the table represent the numbers of instances in each class that have the same prediction cluster and actual cluster.