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Elsevier, Computational Statistics & Data Analysis, (61), p. 124-136

DOI: 10.1016/j.csda.2012.11.018

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A fast algorithm for robust constrained clustering

Journal article published in 2013 by Heinrich Fritz, Luis Angel García Escudero, Agustin Mayo Iscar ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

The application of “concentration” steps is the main principle behind Forgy’s k-means algorithm and Rousseeuw and van Driessen’s fast-MCD algorithm. Despite this coincidence, it is not completely straightforward to combine both algorithms for developing a clustering method which is not severely affected by few outlying observations and being able to cope with non spherical clusters. A sensible way of combining them relies on controlling the relative cluster scatters through constrained concentration steps. With this idea in mind, a new algorithm for the TCLUST robust clustering procedure is proposed which implements such constrained concentration steps in a computationally efficient fashion.