Explain representation of clusters in GRGPF algorithm.

Representation of clusters in GRGPF algorithm :-

• The representation of a cluster in main memory consists of several features.

• Before listing these features, if p is any point in a cluster, let ROWSUM(p) be the sum of the squares of the distances from p to each of the other points in the cluster.

• The following features form the representation of a cluster.

  • N, the number of points in the cluster.
  • The clustroid of the cluster, which is defined specifically to be the point in the cluster that minimizes the sum of the squares of the distances to the other points; that is, the clustroid is the point in the cluster with the smallest ROWSUM.
  • The rowsum of the clustroid of the cluster.

  • For some chosen constant k, the k points of the cluster that are closest to the clustroid, and their rowsums. These points are part of the representation in case the addition of points to the cluster causes the clustroid to change. The assumption is made that the new clustroid would be one of these k points near the old clustroid.

  • The k points of the cluster that are furthest from the clustroid and their rowsums. These points are part of the representation so that we can consider whether two clusters are close enough to merge. The assumption is made that if two clusters are close, then a pair of points distant from their respective clustroids would be close.