Por favor, use este identificador para citar o enlazar este ítem:http://uvadoc.uva.es/handle/10324/21849
Título
A fast algorithm for robust constrained clustering.
Año del Documento
2013
Documento Fuente
Computational Statistics and Data Analysis, 61, 124-136
Zusammenfassung
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.
Materias (normalizadas)
Estadística
Revisión por pares
SI
Idioma
spa
Derechos
openAccess
Aparece en las colecciones
Dateien zu dieser Ressource
Solange nicht anders angezeigt, wird die Lizenz wie folgt beschrieben: Attribution 4.0 International