2006 | OriginalPaper | Chapter
Multi-Objective Clustering and Cluster Validation
Authors : Julia Handl, Joshua Knowles
Published in: Multi-Objective Machine Learning
Publisher: Springer Berlin Heidelberg
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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 identification of groups (or clusters) of homogeneous data items — a process commonly referred to as cluster analysis.