cluster2

CLUSTER ANALYSiS

[Continued...] The best way to gain some intuition into the process of clustering is through some simple examples:

Human beings have an inherent ability to identify clusters in two dimensions. We can clearly see that there are two clusters in this image. Our aim is to teach computers how to emulate this intuition, and then to generalise such capabilities to any number of dimensions.

While this may seem quite simple in principle, it is often very difficult in practice.

Simple clustering methods typically assume equally-sized compact spheroidal clusters. Problems can occur when actual clusters are (a) not of equal size, (b) have complex shapes, or (c) have complex topologies. Agreement with human intuition in such cases generally requires use of more density-based techniques. Of the standard methods, single-link hierarchical clustering is often most suitable.

(a) (b) (c)

Other standard methods suchs as k-means or Ward's method are also valuable. In many common problems, such as categorising customer types, or partitioning land into convenient "postal regions", or defining "codebooks" for compressing data, compact, equally-sized and evenly-spaced clusters are desired. [Continued...]