Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric

Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' for the same functionality using the L1 (Manhattan, taxicab) metric.

RANN

Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees.

This package implements nearest neighbors for the Euclidean (L2) metric. For the Manhattan (L1) metric, install the RANN1 package.

For further details on the underlying ANN library, see https://www.cs.umd.edu/~mount/ANN.

Installation

Released versions

The recommendation is to install the released version from CRAN by doing:

install.packages("RANN")

Bleeding Edge

You can, however, use the remotes package to install the development version:

# install.packages("remotes")
remotes::install_github("jefferis/RANN")

Feedback

Please feel free to:

• submit suggestions and bug-reports at: https://github.com/jefferislab/RANN/issues
• send pull requests after forking: https://github.com/jefferislab/RANN/
• e-mail the maintainer: [email protected]

Copyright and License

see inst/COPYRIGHT and DESCRIPTION files for copyright and license information.