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 <tarnold2@richmond.edu>
LicenseLGPL-2
Version1.5
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("statsmaths/leaderCluster")
statsmaths/leaderCluster documentation built on Jan. 27, 2024, 1:44 p.m.