Use any main-‐memory clustering algorithm to cluster the remaining points and the old RS. Clusters go to the CS; outlying points to the RS.

There are a huge number of clustering algorithms, among them: Density based algorithm, Sub-space clustering, Scale-up methods, Neural networks based methods, Fuzzy clustering, Co …

One established solution is to leverage machine learning, particularly clustering methods. Clustering algorithms are machine learning algorithms that seek to group similar data points …

Clustering is the task of dividing up data points into groups or clusters, so that points in any one group are more \similar" to each other than to points outside the group

We then describe three specific clustering techniques that represent broad categories of algorithms and illustrate a variety of concepts: K-means, agglomerative hierarchical clustering, …

Parametric clustering algorithms (K given) Cost based / hard clustering K-means clustering and the quadratic distortion Model based / soft clustering

Complete-link clustering (also called the diameter, the maximum method or the furthest neighbor method) - methods that consider the distance between two clusters to be equal to the longest …