7 K-Means Cluster Analysis


20211014 Package: kmeans. Chapter Authors: Graham Williams and Gefei Shen.

To identify “natural” groups in population data we often utilise cluster analysis, and the k-means algorithm is an old standard from statistics. This MLHub package demonstrates how k-means works and provides a tool to perform k-means cluster analysis on your own data.

The kmeans package uses sample visualisations and movies to illustrate how the algorithm in progress.

To install, configure, and demonstrate the package:

ml install   davecatmeow/showcase-demo
ml configure kmeans
ml readme    kmeans
ml commands  kmeans
ml demo      kmeans

In addition to the demo command the package also supports train and predict.

Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0.