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NCRN Virtual Seminar: Boosting Models for Edit, Imputation and Prediction of Multiple Response Outcomes Download as iCal file
 
Wednesday, February 05, 2014, 3:00PM - 4:30PM

 

  

 Speaker: John Abowd (Cornell) and Ping Li (Cornell and Rutgers)

Abstract: In this paper, we propose a statistical framework that generalizes the classical logit model to predict multiple responses (i.e., multi-label classification). We develop an effective implementation based on boosting and trees. For the NCRN seminar we present an application to editing and imputation in the multiple response race and ethnicity coding on the American Community Survey.

 

Locations:

 

-Cornell University, Ithaca campus: Ives 381 

For more locations, see http://www.ncrn.info/event/ncrn-virtual-seminar-feb-5-2014

 

Please contact Lars Vilhuber ( This email address is being protected from spambots. You need JavaScript enabled to view it. ) if you wish to participate by video conference, by Monday, February 3, 2014.

 

A recording of the seminar (streaming video) will be available from this link about 5 minutes after the start of the seminar, and will be accessible on-demand afterwards

Location NCRN Videoconferencing, Ives 381
Contact Please RSVP to This email address is being protected from spambots. You need JavaScript enabled to view it.

 

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