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!

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!

Clustering with DBSCAN

Linear Digressions is a podcast about machine learning and data science.  Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.

Technology

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.

Share Clustering with DBSCAN

Sign up to save your podcasts

Clustering with DBSCAN

Clustering with DBSCAN

More shows like Linear Digressions

Stuff You Should Know

Practical AI