statsmaths/leaderCluster: Leader Clustering Algorithm

The leader clustering algorithm provides a means for clustering a set of data points. Unlike many other clustering algorithms it does not require the user to specify the number of clusters, but instead requires the approximate radius of a cluster as its primary tuning parameter. The package provides a fast implementation of this algorithm in n-dimensions using Lp-distances (with special cases for p=1,2, and infinity) as well as for spatial data using the Haversine formula, which takes latitude/longitude pairs as inputs and clusters based on great circle distances.

Getting started

Package details

AuthorTaylor B. Arnold
MaintainerTaylor B. Arnold <[email protected]>
LicenseLGPL-2
Version1.2
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("statsmaths/leaderCluster")
statsmaths/leaderCluster documentation built on May 26, 2017, 5:51 p.m.