ABC-Boost: Adaptive Base Class Boost for Multi-Class Classification

author: Ping Li, Department of Statistical Science, Cornell University
published: Aug. 26, 2009,   recorded: June 2009,   views: 3754
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

Description

We propose ABC-Boost (Adaptive Base Class Boost) for multi-class classification and present ABC-MART, an implementation of ABC-Boost. The original MART (Multiple Additive Regression Trees) algorithm has been popular in certain industry applications (e.g., Web search). For binary classification, ABC-MART recovers MART. For multi-class classification, ABC-MART improves MART, as evaluated on several public data sets.

See Also:

Download slides icon Download slides: icml09_li_abcb_01.pdf (505.1 KB)


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: