Multi-objective clustering and cluster validation

Research output: Chapter in Book/Report/Conference proceedingChapter


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 languageEnglish
Title of host publicationStudies in Computational Intelligence|Stud. Comput. Intell.
PublisherSpringer Nature
Number of pages26
Publication statusPublished - 2006


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