Kmedians: K-Medians
Online, Semi-online, and Offline K-medians algorithms are
given. For both methods, the algorithms can be initialized
randomly or with the help of a robust hierarchical
clustering. The number of clusters can be selected with the
help of a penalized criterion. We provide functions to provide
robust clustering. Function gen_K() enables to generate a sample
of data following a contaminated Gaussian mixture.
Functions Kmedians() and Kmeans() consists in a K-median and a
K-means algorithms while Kplot() enables to produce graph for both
methods.
Cardot, H., Cenac, P. and Zitt, P-A. (2013). "Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm". Bernoulli, 19, 18-43. <doi:10.3150/11-BEJ390>.
Cardot, H. and Godichon-Baggioni, A. (2017). "Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis". Test, 26(3), 461-480 <doi:10.1007/s11749-016-0519-x>.
Godichon-Baggioni, A. and Surendran, S. "A penalized criterion for selecting the number of clusters for K-medians" <doi:10.48550/arXiv.2209.03597>
Vardi, Y. and Zhang, C.-H. (2000). "The multivariate L1-median and associated data depth". Proc. Natl. Acad. Sci. USA, 97(4):1423-1426. <doi:10.1073/pnas.97.4.1423>.
| Version: |
2.2.0 |
| Imports: |
foreach, doParallel, parallel, genieclust, Gmedian, mvtnorm, capushe, ggplot2, reshape2 |
| Published: |
2023-12-18 |
| DOI: |
10.32614/CRAN.package.Kmedians |
| Author: |
Antoine Godichon-Baggioni [aut, cre, cph],
Sobihan Surendran [aut] |
| Maintainer: |
Antoine Godichon-Baggioni <antoine.godichon_baggioni at upmc.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
Kmedians results |
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