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A new approach to classification

Walker, Stephen G., Fuentes-Garcia, Ruth (2010) A new approach to classification. Journal of Applied Statistics, 37 (1). pp. 137-146. ISSN 0266-4763. (doi:10.1080/02664760802698987) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:23908)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1080/02664760802698987

Abstract

Clustering is a common and important issue, and finite mixture models based on the normal distribution are frequently used to address the problem. In this article, we consider a classification model and build a mixture model around it. A good assessment of the allocation of observations and number of clusters is easily obtained from this approach.

Item Type: Article
DOI/Identification number: 10.1080/02664760802698987
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Funders: Universidad Nacional de Moquegua (https://ror.org/05v2asf50)
Depositing User: Stephen Walker
Date Deposited: 29 Jun 2011 13:37 UTC
Last Modified: 12 Jul 2022 10:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/23908 (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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