The process of grouping a set of physical or abstract objects
into classes of similar objects is called clustering. A cluster is a
collection of data objects that are similar to one another within
the same cluster and are dissimilar to the objects in other
clusters. A cluster of data objects can be treated collectively
as one group. Although classification is an effective means for
distinguishing groups or classes of objects, often it requires
costly method for collection and labelling of a large set of
training tuples or patterns, which the classifier uses to model
each group. It is often more desirable to proceed in the
reverse direction owing to the fact that most of the real world
datasets are unsupervised.