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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.3 |
2026-04-09 windows/windows R-4.5 | densityClust_0.3.3.zip |
235.9 KiB |