Cluster Analysis

Wolfgang Karl Härdle and Zdeněk Hlávka
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Wolfgang Karl Härdle: Humboldt-Universität zu Berlin, C.A.S.E. Centre f. Appl. Stat. & Econ. School of Business and Economics
Zdeněk Hlávka: Charles University in Prague, Faculty of Mathematics and Physics Department of Statistics

Chapter Chapter 13 in Multivariate Statistics, 2015, pp 225-244 from Springer

Abstract: Abstract When considering groups of objects in a multivariate data set, two situations can arise. Given a data set containing measurements on individuals, in some cases we want to see if some natural groups or classes of individuals exist, and in other cases, we want to classify the individuals according to a set of existing groups. Cluster analysis develops tools and methods concerning the former case, that is, given a data matrix containing multivariate measurements on a large number of individuals (or objects), the objective is to build subgroups or clusters of individuals. This is done by grouping individuals that are “similar” according to some appropriate criterion.

Keywords: Single Linkage; Complete Linkage; Outlying Observation; Ward Method; Auto Theft (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-642-36005-3_13

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