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Classifying classification problems

Gower, John (2004). Classifying classification problems. In: Comptes Rendus des Iles Rencontres de la Societe Francophone de Classification (Chavent, M; Dordan, O; Lacomblez, C.C.; Langlais, M and Patouille, B eds.), Information not provided, pp. 41–47.

URL: http://www.sfc-classification.net/IMG/pdf/Actes_SF...
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Abstract

Classification problems, both for assignment and class construction, are specified either in probabilistic form or not. Underlying issues are (i) the types of sampling unit under consideration: in particular, are they differentiated into previously determined classes (possibly with identical members) or are they undifferentiated and (ii) considerations of the types of variable used; are they quantitative or categorical? Rather than a simple data-matrix, the fundamental form of data is taken to be the between and within-group structure. These considerations lead to a simple cross-classification of familiar, and some novel, classification problems.

Item Type: Conference Item
Copyright Holders: 2004 The Author
Keywords: probabilistic classification; non-probabilistic classification; classes; groups; assignment; class construction; approximation
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
Item ID: 22605
Depositing User: Sarah Frain
Date Deposited: 26 Aug 2010 14:08
Last Modified: 15 Jan 2016 14:46
URI: http://oro.open.ac.uk/id/eprint/22605
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