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

A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based 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 (global-local outlier score from hierarchies). 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. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.

Version:	1.2.7
Depends:	R (≥ 4.3.0)
Imports:	generics, graphics, Rcpp (≥ 1.0.11), stats
LinkingTo:	Rcpp
Suggests:	dendextend, fpc, igraph, knitr, microbenchmark, reticulate (≥ 1.41), rmarkdown, testthat (≥ 3.0.0), tibble, tidyverse
Published:	2026-10-05
DOI:	10.32614/CRAN.package.dbscan
Author:	Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph], Claudia Malzer [ctb]
Maintainer:	Michael Hahsler <mhahsler at lyle.smu.edu>
BugReports:	https://github.com/mhahsler/dbscan/issues
License:	GPL (≥ 3)
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.
URL:	https://github.com/mhahsler/dbscan, http://michael.hahsler.net/dbscan/
NeedsCompilation:	yes
Citation:	dbscan citation info
Materials:	README, NEWS
In views:	AnomalyDetection, Cluster
CRAN checks:	dbscan results

Documentation:

Reference manual:

dbscan.html , dbscan.pdf

Vignettes:

Getting started with dbscan (source, R code) Using Hierarchical DBSCAN (HDBSCAN) (source, R code) Nearest-Neighbor Search and Graphs (source, R code) Nearest-Neighbor Clustering with jpclust and sNNclust (source, R code) Ordering Points With OPTICS (source, R code) Outlier Detection with dbscan (source, R code) Using dbscan from Python (source, R code) Using dbscan with tidyverse (source, R code) Fast Density-based Clustering (DBSCAN and OPTICS) (source, R code)

Downloads:

Package source:	dbscan_1.2.7.tar.gz
Windows binaries:	r-devel: dbscan_1.2.6.zip, r-release: dbscan_1.2.6.zip, r-oldrel: dbscan_1.2.6.zip
macOS binaries:	r-release (arm64): dbscan_1.2.6.tgz, r-oldrel (arm64): dbscan_1.2.6.tgz, r-release (x86_64): not available, r-oldrel (x86_64): dbscan_1.2.6.tgz
Old sources:	dbscan archive

Reverse dependencies:

Reverse imports:

AnimalSequences, autoFlagR, bioregion, CLONETv2, clusterWebApp, cordillera, CPC, crosshap, crownsegmentr, CspStandSegmentation, cyclicwave, daltoolbox, dobin, dPCP, emcAdr, eventstream, evprof, fdacluster, flowcluster, FORTLS, funtimes, HaploVar, immunaut, karyotapR, LLMing, LOMAR, maotai, mditools, metaCluster, neuroim2, oclust, omicsTools, openSkies, outlierMBC, ParBayesianOptimization, pguIMP, phynotype, PiC, quickOutlier, rarefun, rcrisp, Rhobots, riemannianStats, rMultiNet, sfhotspot, smotefamily, snap, spCF, spNetwork, squat, ssel, ssMRCD, STATassist, stdbscan, stream, SuperCell, synr, tidylearn, tidySEM, tlsR, VBphenoR, VIProDesign, weird

Reverse suggests:

clayringsmiletus, DataSimilarity, diceR, discoCVI, doc2vec, DrData, EHRtemporalVariability, fastml, FCPS, flownet, FuelDeep3D, ksharp, MapperAlgo, metasnf, mlr3cluster, opticskxi, OTclust, outlierensembles, pagoda2, parameters, performance, R4VN, riskutility, rtemis, SampleCore, seriation, sfdep, sfnetworks, sharp, spdep, specmine, tbnb, TextAnalysisR, tidyclust

Linking:

Please use the canonical form https://CRAN.R-project.org/package=dbscan to link to this page.