MCC — multiple correlation clustering

Doyle, John R. 1992. MCC — multiple correlation clustering. International Journal of Man-Machine Studies 37 (6) , pp. 751-765. 10.1016/0020-7373(92)90066-T

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Abstract

A clustering algorithm is described which is powerful, in that at each iterative step of the method global information is used to constrain the algorithm's convergence towards a solution. It is stable in the face of missing data in the input; it is efficient in that it will extract a small signal from a lot of noise; it is impervious to multicolinearity; it may be used in two-way clustering. Each of these claims is illustrated by its application to different data sets. Despite these advantages, the algorithm is easy to implement and understand: it is sufficient to know what a correlation coefficient is in order to understand the guts of the algorithm. Because the program repeatedly correlates correlation matrices it is called here Multiple Correlation Clustering, or MCC for short.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Business (Including Economics)
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher:	Elsevier
ISSN:	0020-7373
Last Modified:	05 Nov 2019 03:30
URI:	https://orca.cardiff.ac.uk/id/eprint/37792

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