EPISODE · Nov 20, 2017 · 16 MIN
Clustering with DBSCAN
from Linear Digressions · host 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!
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