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dbscan (version 0.9-3)

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

Description

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 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.

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Version

Install

install.packages('dbscan')

Monthly Downloads

30,029

Version

0.9-3

License

GPL (>= 2)

Maintainer

Michael Hahsler

Last Published

September 3rd, 2015

Functions in dbscan (0.9-3)

kNNdist

Calculate and plot the k-Nearest Neighbor Distance
frNN

Find the Fixed Radius Nearest Neighbors
optics

OPTICS
lof

Local Outlier Factor Score
kNN

Find the k Nearest Neighbors
dbscan

DBSCAN