Nothing
dbscan: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Version 1.1-1
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 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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph] |
| Date of publication | 2017-03-19 23:26:00 UTC |
| Maintainer | Michael Hahsler <mhahsler@lyle.smu.edu> |
| License | GPL (>= 2) |
| Version | 1.1-1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the dbscan package in your browser
Any scripts or data that you put into this service are public.
