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A novel initialisation based on hospital-resident assignment for the k-modes algorithm

Gillard, Jonathan ORCID:, Knight, Vincent ORCID: and Wilde, Henry 2023. A novel initialisation based on hospital-resident assignment for the k-modes algorithm. Soft Computing 27 , pp. 9441-9457. 10.1007/s00500-023-08407-2

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This paper presents a new way of selecting an initialisation for the k-modes algorithm that allows for a notion of game theoretic fairness that classic initialisations, namely those by Huang and Cao, do not. Our new method utilises the hospital-resident assignment problem to find the set of initial cluster centroids which we compare with two classical initialisation methods for k-modes: the original presented by Huang and the next most popular method of Cao and co-authors. To highlight the merits of our proposed method, two stages of analysis are presented. It is demonstrated that the proposed method is often able to offer computational speed-up of the order of 50%. Improved clustering, in terms of a commonly used cost-function, was witnessed in several cases and can be of the order of 10%, particularly for more complex datasets.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Publisher: Springer
ISSN: 1432-7643
Date of First Compliant Deposit: 2 May 2023
Date of Acceptance: 2 May 2023
Last Modified: 16 Jun 2023 11:11

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