Abstract
This chapter is concerned with unsupervised classification, that is, the analysis of data sets for which no (or very little) training data is available. The main goals in this data-driven type of analysis are the discovery of a data set's underlying structure, and the identi.cation of groups (or clusters) of homogeneous data items - a process commonly referred to as cluster analysis. © 2006 Springer-Verlag Berlin Heidelberg.
| Original language | English |
|---|---|
| Title of host publication | Studies in Computational Intelligence|Stud. Comput. Intell. |
| Publisher | Springer Nature |
| Pages | 21-47 |
| Number of pages | 26 |
| Volume | 16 |
| DOIs | |
| Publication status | Published - 2006 |