R package 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.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Michael C. Thrun, Quirin Stier: Fundamental clustering algorithms suite (2021) not zbMATH
- Almodóvar-Rivera, Israel A.; Maitra, Ranjan: Kernel-estimated nonparametric overlap-based syncytial clustering (2020)