Clustering with DBSCAN - a podcast by Ben Jaffe and Katie Malone

DBSCAN is a density-based clustering algorithm for doing unsupervised learning. It's pretty nifty: with just two parameters, you can specify "dense" regions in your data, and grow those regions out organically to find clusters. In particular, it can fit irregularly-shaped clusters, and it can also identify outlier points that don't belong to any of the clusters. Pretty cool!

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone