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Mathematical Underpinnings of AnalyticsTheory and Applications$
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Peter Grindrod

Print publication date: 2014

Print ISBN-13: 9780198725091

Published to Oxford Scholarship Online: March 2015

DOI: 10.1093/acprof:oso/9780198725091.001.0001

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Clustering and unsupervised classification

Clustering and unsupervised classification

Chapter:
(p.125) 4 Clustering and unsupervised classification
Source:
Mathematical Underpinnings of Analytics
Author(s):

Peter Grindrod CBE

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198725091.003.0005

This chapter examines iterative clustering methods including finite mixture modelling based on the EM algorithm. Applications to behavioural segmentation of domestic energy customers, the identification of customer missions in supermarkets, and behaviour-based targeting for mobile network operators are covered.

Keywords:   K-means cluster, EM algorithm, finite mixture modelling, behavioural segmentation, energy demand, mobile phone usage, customer shopping missions

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