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

Table 8

Comparison of cluster accuracy on the Lym dataset.

Parameter settings	k-prototypes	EKACMD	WKPCA
k = 2	0.545247	0.542292	—
k = 4	0.572702	0.604324	0.668918
k = 6	0.529730	0.574324	—
k = 8	0.625945	0.661621	—
k = 10	0.600000	0.651351	—