Modern Trends in Data Mining

As their ability to capture and organize large amounts of data

increases, organizations rely more on datamining technology to learn

from this valuable resource. We will give several examples of this

process, based on our our own experiences. This talk will give a

brief overview of some of the most promising new methods for

"supervised" learning, including the lasso, random forests, boosting,

and SVMs.

 
Date and Time:
 Monday, November 6, 2006.  4:15 PM.
Approximate duration of 1 hour(s).
Location:
Bldg 380, Room 380C (basement) Refreshments served at 4:00PM in the courtyard outside Room 380C   [Map]
URL:
Audience:
Faculty/Staff
Students
Category:
Other
Conferences/Symposia
Sponsor:
Institute for Mathematical and Computational Engineering (iCME) and Statistics Department
Contact:
650-725-8594
chanaart@stanford.edu
Download:
Print:
Last Modified:
October 30, 2006