CRAN/E | dbscan

dbscan

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

Installation

About

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.

Citation dbscan citation info
github.com/mhahsler/dbscan
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.
Bug report File report

Key Metrics

Version 1.1-12
Published 2023-11-28 150 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks dbscan results

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Maintainer

Maintainer

Michael Hahsler

mhahsler@lyle.smu.edu

Authors

Michael Hahsler

aut / cre / cph

Matthew Piekenbrock

aut / cph

Sunil Arya

ctb / cph

David Mount

ctb / cph

Material

README
NEWS
Reference manual
Package source

In Views

Cluster

Vignettes

Hierarchical DBSCAN (HDBSCAN) with the dbscan package
Fast Density-based Clustering (DBSCAN and OPTICS)

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

dbscan archive

Imports

Rcpp ≥ 1.0.0
graphics
stats

Suggests

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LinkingTo

Rcpp

Reverse Depends

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