Recitation 8: Hierarchical and k-means Clustering

author: Mitchell A. Peabody, Massachusetts Institute of Technology, MIT
recorded by: Massachusetts Institute of Technology, MIT
published: Oct. 29, 2012,   recorded: April 2011,   views: 2187
released under terms of: Creative Commons Attribution Non-Commercial Share Alike (CC-BY-NC-SA)
Categories

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Topics covered: Unsupervised learning, k-means clustering, distance metric, cluster merging, centroid, k-mean error, hold out set, k value significance, features of k-means clustering, merits and disadvantages of types of clustering.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: