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MS Final Examination – Jafer Almuallim


Wednesday, June 12, 2013 9:00 AM - 11:00 AM

Classifier Chains for Multi-Label Classification with Incomplete Label Assignment
Many methods have been explored the literature of multi-label learning. Ranging from simple problem transformation to more complex method that capture correlation among labels. However, mostly all present work do not address the challenge with incomplete labeled data. The goal of this project is to extend the work of ensemble classifier chain to learn models using training examples with incomplete label assignment. This scenario is highly expected in many real-world application. For example, in image annotation, a user provides partial tag assignment labels for the image. We propose a new method that considers the multi-label learning problem in which portion of label assignment is missing. A further evaluation is covered in this project to study the effect of different parameter accompany this approach.

Major Advisor: Xiaoli Fern
Committee: Raviv Raich
Committee: Weng-Keen Wong 


Kelley Engineering Center (campus map)
1005
Nicole Thompson
1 541 737 3617
Nicole.Thompson at oregonstate.edu
Sch Elect Engr/Comp Sci
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