DaSSWeb – Data Science and Statistics Webinar
Tuesday 26 October, 14:30
Speaker: Nuno Moniz
Researcher INESC TEC Invited Professor @ Faculty of Sciences, University of Porto Invited Professor @ Faculty of Engineering, University of Porto
Title: Is there a free lunch in imbalanced learning?
Zoom link: videoconf-colibri.zoom.us/j/89767753105
<videoconf-colibri.zoom.us/j/87373848710> Abstract: The ability to predict rare events remains one of the most challenging tasks to solve in machine learning. For almost three decades, research in imbalanced learning has produced many strategies to help in this endeavour. The most popular – resampling strategies – work by creating new data sets where the original data is biased towards cases describing rare events having higher probability. Today, it would seem that both research and industry have widespread assumptions concerning which are the “best” or “worst” strategies. In this talk, we will set up a face-to-face between theory and practice. First, we will leverage the concept of no free lunch to analyse if we can assume there are resampling strategies more likely to be the best in solving imbalanced learning problems. Second, we will evaluate if data characteristics can help us automatically decide which strategies are most likely to produce the best outcome in unseen data.
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