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dbscan (version 0.9-1)

Density Based Clustering of Applications with Noise (DBSCAN)

Description

A fast reimplementation of the density-based DBSCAN clustering algorithm for spatial data introduced by Ester et al. 'A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise,' 1996. This implementation uses the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. The implementation is many times faster than the R-based implementation in package fpc.

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Version

Install

install.packages('dbscan')

Monthly Downloads

30,029

Version

0.9-1

License

GPL (>= 2)

Maintainer

Michael Hahsler

Last Published

July 23rd, 2015

Functions in dbscan (0.9-1)

kNNdist

Calculate and plot the k-Nearest Neighbor Distance
dbscan

DBSCAN