Database Reference
In-Depth Information
Final cluster assignments for K-means++
Variants
There are many other variants of K-means; they focus on initialization methods or the
core model. One of the more common variants is fuzzy K-means. This model does not as-
sign each point to one cluster as K-means does (a so-called hard assignment). Instead, it is
a soft version of K-means, where each point can belong to many clusters, and is represen-
ted by the relative membership to each cluster. So, for K clusters, each point is represen-
ted as a K-dimensional membership vector, with each entry in this vector indicating the
membership proportion in each cluster.
