dbscan : Fast Density-Based Clustering with R

This article describes the implementation and use of the R package dbscan, which provides complete and fast implementations of the popular density-based clustering algorithm DBSCAN and the augmented ordering algorithm OPTICS. Package dbscan uses advanced open-source spatial indexing data structures...

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Veröffentlicht in:Journal of statistical software Jg. 91; H. 1; S. 1 - 30
Hauptverfasser: Hahsler, Michael, Piekenbrock, Matthew, Doran, Derek
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Foundation for Open Access Statistics 01.10.2019
Schlagworte:
dbscan
density-based clustering
hierarchical clustering
optics
ISSN:1548-7660, 1548-7660
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Zusammenfassung:This article describes the implementation and use of the R package dbscan, which provides complete and fast implementations of the popular density-based clustering algorithm DBSCAN and the augmented ordering algorithm OPTICS. Package dbscan uses advanced open-source spatial indexing data structures implemented in C++ to speed up computation. An important advantage of this implementation is that it is up-to-date with several improvements that have been added since the original algorithms were publications (e.g., artifact corrections and dendrogram extraction methods for OPTICS). We provide a consistent presentation of the DBSCAN and OPTICS algorithms, and compare dbscan's implementation with other popular libraries such as the R package fpc, ELKI, WEKA, PyClustering, SciKit-Learn, and SPMF in terms of available features and using an experimental comparison.
ISSN:1548-7660
1548-7660
DOI:10.18637/jss.v091.i01