RT info:eu-repo/semantics/article
T1 A fast algorithm for robust constrained clustering.
A1 Fritz, Heinrich
A1 García Escudero, Luis Ángel
A1 Mayo Iscar, Agustín
K1 Estadística
K1 Cluster analysis
K1 Robustness
K1 Impartial trimming
K1 Classification EM algorithm
K1 TCLUST
AB The application of “concentration” steps is the main principle behind Forgy’sk-means algorithm and Rousseeuw and van Driessen’s fast-MCD algorithm.Despite this coincidence, it is not completely straightforward to combine bothalgorithms for developing a clustering method which is not severely affectedby few outlying observations and being able to cope with non spherical clusters.A sensible way of combining them relies on controlling the relative clusterscatters through constrained concentration steps. With this idea in mind,a new algorithm for the TCLUST robust clustering procedure is proposedwhich implements such constrained concentration steps in a computationallyefficient fashion.
PB Elsevier
SN 0167-9473
YR 2013
FD 2013
LK http://uvadoc.uva.es/handle/10324/21849
UL http://uvadoc.uva.es/handle/10324/21849
LA eng
NO Computational Statistics and Data Analysis, 2013, vol. 61, p. 124-136
NO Producción Científica
DS UVaDOC
RD 03-abr-2025