concept k - mean clustering in category R

This is an excerpt from Manning's book Machine Learning with R, the tidyverse, and mlr. Login to get full access to this book.

Figure 16.1. Five iterations of k-means clustering. In the top-left plot, three initial centers are randomly generated in the feature space (crosses). Cases are assigned to the cluster of their nearest center. At each iteration, each center moves to the mean of the cases in its cluster (indicated by arrows). The feature space can be partitioned up into Voronoi cells (I'll discuss these shortly), indicated by the shaded regions, that show regions of the feature space closest to a particular centroid.

The strengths of k-means clustering are as follows: