Cluster analysis itself is not one specific algorithm, but the general task to be solved.It can be achieved by various algorithms that differ significantly in their notion of what constitutes a cluster and how to efficiently find them.In either case 'port' corresponds to the primary port number being used by the group.
If the application protocol is not listed in the registry, an OID value of the form or are used for TCP-based and UDP-based protocols, respectively.
Popular notions of clusters include groups with small distances among the cluster members, dense areas of the data space, intervals or particular statistical distributions.
Clustering can therefore be formulated as a multi-objective optimization problem.
The subtle differences are often in the usage of the results: while in data mining, the resulting groups are the matter of interest, in automatic classification the resulting discriminative power is of interest.
Cluster analysis was originated in anthropology by Driver and Kroeber in 1932 and introduced to psychology by Zubin in 1938 and Robert Tryon in 1939 There is a common denominator: a group of data objects.