K-means clustering in R
See Video ⮞ ☝ AGRON Stats Lectures June 26, 2018 Introduction Import data file Observe data & format variables k-means Clustering Determine and visualize the optimal number of clusters Computing k-means clusters on a data matrix Directly computing means using aggregate function Point classifcation of original data Introduction \(K-means\) clustering is a method of vector quantization, originally from signal processing, that aims to partition \(n\) observations into \(k\) clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. In other words, the \(k-means\) algorithm identifies \(k\) number of centroids, and then allocates every data point to the nearest cluster, while keeping the centroids as small as possible. Let's get started Import data file I often recommend to firs...