A fast reimplementation of several densitybased algorithms of the DBSCAN family for spatial data. Includes the clustering algorithms DBSCAN (densitybased spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), and the outlier detection algorithm LOF (local outlier factor). The implementations use the kdtree data structure (from library ANN) for faster knearest neighbor search. An R interface to fast kNN and fixedradius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.
Package details 


Author  Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph] 
Maintainer  Michael Hahsler <mhahsler@lyle.smu.edu> 
License  GPL (>= 2) 
Version  1.16 
URL  https://github.com/mhahsler/dbscan 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.