Table 1.

Sub-problems and RCs for generic clustering algorithm design.

Sub-problem	Reusable components
Initialize representatives	DIANA, RANDOM, XMEANS, GMEANS, PCA, KMEANS++, SPSS
Measure distance	EUCLIDEAN, CITY, CORREL, COSINE
Update representatives	MEAN, MEDIAN, ONLINE
Evaluate clusters	AIC, BIC, SILHOU, COMPACT, XB, CONN