Linear Digressions   /     Clustering with DBSCAN

Description

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!

Subtitle
DBSCAN is a density-based clustering algorithm fo…
Duration
00:16:14
Publishing date
2017-11-20 03:08
Link
http://feedproxy.google.com/~r/udacity-linear-digressions/~3/9NYWQgzkPmU/clustering-with-dbscan
Contributors
  Ben Jaffe and Katie Malone
author  
Enclosures
http://feedproxy.google.com/~r/udacity-linear-digressions/~5/0uOu8eMS1Ko/358247057-linear-digressions-clustering-with-dbscan.mp3
audio/mpeg