dbscan: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms

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 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.

Version: 1.0-0
Imports: Rcpp, graphics, stats, methods
LinkingTo: Rcpp
Suggests: fpc, microbenchmark, testthat, dendextend
Published: 2017-02-03
Author: Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph]
Maintainer: Michael Hahsler <mhahsler at lyle.smu.edu>
BugReports: https://github.com/mhahsler/dbscan/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: ANN library is copyright by University of Maryland, Sunil Arya and David Mount. All other code is copyright by Michael Hahsler and Matthew Piekenbrock.
NeedsCompilation: yes
Materials: README NEWS
In views: Cluster
CRAN checks: dbscan results


Reference manual: dbscan.pdf
Vignettes: Fast Density-based Clustering
Package source: dbscan_1.0-0.tar.gz
Windows binaries: r-devel: dbscan_1.0-0.zip, r-release: dbscan_1.0-0.zip, r-oldrel: dbscan_1.0-0.zip
OS X Mavericks binaries: r-release: dbscan_1.0-0.tgz, r-oldrel: dbscan_1.0-0.tgz
Old sources: dbscan archive

Reverse dependencies:

Reverse imports: AFM, gsrc, haploReconstruct, largeVis, stream
Reverse suggests: smotefamily


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