Machine Learning with R, the tidyverse, and mlr

Chapter 18. Clustering based on density: DBSCAN and OPTICS

This chapter covers

• Understanding density-based clustering
• Using the DBSCAN and OPTICS algorithms

Our penultimate stop in unsupervised learning techniques brings us to density-based clustering. Density-based clustering algorithms aim to achieve the same thing as k-means and hierarchical clustering: partitioning a dataset into a finite set of clusters that reveals a grouping structure in our data.

In the last two chapters, we saw how k-means and hierarchical clustering identify clusters using distance: distance between cases, and distance between cases and their centroids. Density-based clustering comprises a set of algorithms that, as the name suggests, uses the density of cases to ...