A fast reimplementation of several densitybased algorithms of the DBSCAN family. 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), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (globallocal outlier score from hierarchies). 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  1.111 
URL  https://github.com/mhahsler/dbscan 
Package repository  View on CRAN 
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