README.md

In zhaodyleo/Kmeans: The package will perform the kmeans cluster on the data matrix

Kmeans

k-means clustering is a method of vector quantization that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid)

There are three functions include in this library which are

• kmeans_cluster: training the model to determine the center for each cluster and the cluster each observations it belongs.
• kmeans_cluster_predict: using the center to determine the cluster new data belongs
• kmeans_label_rematch: match the trained cluster label with the actual cluster label.

Check the detail information for each functions through help page or vignettes.

How to install the library

To install the development version of Kmeans from GitHub using devtools:

library(devtools)
install_github("zhaodyleo/Kmeans")

Vignettes and examples

To build the vignettes for kmeans during installation from GitHub, use the following command:

library(devtools)
install_github("zhaodyleo/Kmeans", build_vignettes = TRUE)

The Kmeans vignettes can then be accessed via the following commands:

vignette("kmeans_Leo")

zhaodyleo/Kmeans documentation built on Dec. 23, 2021, 9:18 p.m.