Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6870818 | Computational Statistics & Data Analysis | 2013 | 13 Pages |
Abstract
The application of “concentration” steps is the main principle behind Forgy's k-means algorithm and the 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.
Keywords
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Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Heinrich Fritz, Luis A. GarcÃa-Escudero, AgustÃn Mayo-Iscar,