R for Everyone: Advanced Analytics and Graphics, 2nd Edition

25. Clustering

Clustering, which plays a big role in modern machine learning, is the partitioning of data into groups. This can be done in a number of ways, the two most popular being K-means and hierarchical clustering. In terms of a data.frame, a clustering algorithm finds out which rows are similar to each other. Rows that are grouped together are supposed to have high similarity to each other and low similarity with rows outside the grouping.

25.1 K-means

One of the more popular algorithms for clustering is K-means. It divides the observations into discrete groups based on some distance metric. For this example, we use the wine dataset from the University of California–Irvine Machine Learning Repository, available at http://archive.ics.uci.edu/ml/datasets/Wine ...