Support vector clustering - Scholarpedia

The objective of clustering is to partition a data set into groups according to some criterion in an attempt to organize data into a more meaningful form. There are many ways of achieving this goal. Clustering may proceed according to some parametric model or by grouping points according to some distance or similarity measure as in hierarchical clustering. A natural way to put cluster boundaries is in regions in data space where there is little data, i.e. in "valleys" in the probability distribution of the data. This is the path taken in support vector clustering (SVC), which is based on the support vector approach (see Ben-Hur et al., 2001).