An improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100, 000 samples) very efficiently. It was initially implemented by Thomas Lin Pedersen, with inputs from Sean Hughes and later improved by Xiaojie Qiu to handle large datasets with kNNs.
Version: | 0.3 |
Imports: | Rcpp, FNN, Rtsne, ggplot2, ggrepel, grDevices, gridExtra, RColorBrewer |
LinkingTo: | Rcpp |
Suggests: | testthat |
Published: | 2017-10-24 |
Author: | Thomas Lin Pedersen [aut, cre], Sean Hughes [aut], Xiaojie Qiu [aut] |
Maintainer: | Thomas Lin Pedersen <thomasp85 at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | densityClust results |
Reference manual: | densityClust.pdf |
Package source: | densityClust_0.3.tar.gz |
Windows binaries: | r-devel: densityClust_0.3.zip, r-release: densityClust_0.3.zip, r-oldrel: densityClust_0.3.zip |
OS X El Capitan binaries: | r-release: densityClust_0.3.tgz |
OS X Mavericks binaries: | r-oldrel: densityClust_0.3.tgz |
Old sources: | densityClust archive |
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