dbscan v0.9-1


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by Michael Hahsler

Density Based Clustering of Applications with Noise (DBSCAN)

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.

Functions in dbscan

Name Description
kNNdist Calculate and plot the k-Nearest Neighbor Distance
dbscan DBSCAN
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Date 2015-07-21
Copyright ANN library is copyright University of Maryland, Sunil Arya and David Mount.
License GPL (>= 2)
LinkingTo Rcpp
NeedsCompilation yes
Packaged 2015-07-22 14:48:10 UTC; hahsler
Repository CRAN
Date/Publication 2015-07-23 06:58:07

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