dbscan: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Version 1.1-1

A fast reimplementation of several density-based algorithms of the DBSCAN family for spatial data. Includes the DBSCAN (density-based spatial clustering of applications with noise) and OPTICS (ordering points to identify the clustering structure) clustering algorithms HDBSCAN (hierarchical DBSCAN) and the LOF (local outlier factor) algorithm. The implementations uses the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.

Package details

AuthorMichael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph]
Date of publication2017-03-19 23:26:00 UTC
MaintainerMichael Hahsler <mhahsler@lyle.smu.edu>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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dbscan documentation built on May 30, 2017, 5:45 a.m.