 The task of supervised classification involves extracting information from the labeled examples that allows accurate prediction of class labels of future examples.This may involve the abstraction of a rule or concept relating observed object features to category labels, or it may not involve abstraction (e.g., exemplar models).The task of clustering involves recognizing inherent structure in a data set and grouping objects together by similarity into classes.