Last week we said goodbye to Learning to Rank, by discussing Thurstone’s models, the Plackett-Luce model, ListNet and the LeToR test.

During today’s meeting we introduced the problem of Imbalanced Learning, and discussed some initial ideas on how to deal with imbalanced classes in Machine Learning. We will be concentrating on this topic for the next few weeks and learn about measures for imbalanced classification and algorithm-level approaches to the problem.

If you’re interested in exploring Imbalanced Learning with us, we’ll be meeting as usual on Thursdays, 4:50PM in 423WE.