Many algorithms are designed to cluster numerical data Applications may require clustering other types of data: binary, categorical (nominal), and ordinal data, or mixtures of these data types

Cluster analysis is to find hidden categories. A hidden category (i.e., probabilistic cluster) is a distribution over the data space, which can be mathematically represented using a probability …

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.

Supercomputer/High Performance Computing (HPC) cluster: A collection of similar computers connected by a high speed interconnect that can act in concert with each other.

Cluster analysis is concerned with forming groups of similar objects based on several measurements of different kinds made on the objects. The key idea is to identify …

Cluster Analysis: Basic Concepts and Algorithms What is Cluster Analysis? Finding groups of objects such that the objects in a group will be similar (or related) to one another and different …

A cluster is a set of objects such that an object in a cluster is closer (more similar) to the “center” of a cluster, than to the center of any other cluster