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 HDBSCAN (hierarchical DBSCAN) and the LOF (local outlier factor) algorithm. The implementations use 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: 1.1-3
Imports: Rcpp (≥ 0.12.12), graphics, stats, methods
LinkingTo: Rcpp
Suggests: fpc, microbenchmark, testthat, dendextend, igraph, knitr, DMwR
Published: 2018-11-13
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
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
SystemRequirements: C++11
Materials: README NEWS
In views: Cluster
CRAN checks: dbscan results


Reference manual: dbscan.pdf
Vignettes: HDBSCAN with the dbscan package
Fast Density-based Clustering
Package source: dbscan_1.1-3.tar.gz
Windows binaries: r-devel: dbscan_1.1-3.zip, r-release: dbscan_1.1-3.zip, r-oldrel: dbscan_1.1-3.zip
OS X binaries: r-release: dbscan_1.1-3.tgz, r-oldrel: dbscan_1.1-3.tgz
Old sources: dbscan archive

Reverse dependencies:

Reverse imports: AFM, cordillera, DDoutlier, diceR, funtimes, haploReconstruct, ParBayesianOptimization, projector, smotefamily, stream
Reverse suggests: supc


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