To summarize the SBC-based initial training set generation algorithm, let U={U 1 , U 2 , …, U N } be the set of unlabeled examples to be clustered, and k be the predefined size of initial training data set.
sBC technique selects k most representative unlabeled examples from U to generate the initial training data set.