silverfoxxxx/package1: K Means Clustering on Data Matrix

This package inputs a numeric data matrix x and an explicit integer k for the number of clusters. k means clustering includes 4 steps: Initialization: Select K random "centroids" from points Assignment: Each point is assigned to nearest centroids cluster using Euclidean distance. Update: Calculate the cluster mean to be new centroids. Repeat Assignment and Update to convergence of centroids at tolerance level (default is 1e-5).

install.packages("remotes")
remotes::install_github("silverfoxxxx/package1")