GNU R clustering by fast search and find of density peaks
DescriptionAn 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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