Analysis of Clustering Procedures

author: Sanjoy Dasgupta, Department of Computer Science and Engineering, UC San Diego
published: July 30, 2009,   recorded: June 2009,   views: 1273
Categories

Slides

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.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 1:09:45
!NOW PLAYING
Watch Part 2
Part 2 53:52
!NOW PLAYING
Watch Part 3
Part 3 24:12
!NOW PLAYING

Description

Clustering procedures are notoriously short on rigorous guarantees. In this tutorial, I will cover some of the types of analysis that have been applied to clustering, and emphasize open problems that remain. Part I. Approximation algorithms for clustering Two popular cost functions for clustering are k-center and k-means. Both are NP-hard to optimize exactly. (a) Algorithms for approximately optimizing these cost functions. (b) Hierarchical versions of such clusterings. (c) Clustering when data is arriving in a streaming or online manner. Part II. Analysis of popular heuristics (a) How good is k-means? How fast is it? (b) Probabilistic analysis of EM. (c) What approximation ratio is achieved by agglomerative heuristics for hierarchial clustering? Part III. Statistical theory in clustering What aspects of the underlying data distribution are captured by the clustering of a finite sample from that distribution? (a) Consistency of k-means. (b) The cluster tree and linkage algorithms. (c) Rates for vector quantization.

See Also:

Download slides icon Download slides: mlss09us_dasgupta_acp.pdf (626.7┬áKB)


Help icon Streaming Video Help

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: