densityClust: Clustering by Fast Search and Find of Density Peaks
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 |
Downloads:
Reverse dependencies:
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