Weighted k-Prototypes Clustering Algorithm Based on the Hybrid Dissimilarity Coefficient

Table 9

Comparison of cluster accuracy on the ACA dataset.

Parameter settings	k-prototypes	EKACMD	WKPCA
k = 2	0.532330	0.552706	0.582608
k = 4	0.682198	0.692898	—
k = 6	0.669710	0.678260	—
k = 8	0.700000	0.708695	—
k = 10	0.697101	0.700000	—