报 告 人：张朝阳，美国南密西西比大学(The University of Southern Mississippi, USA)教授
报告题目：Imbalanced Data Handling Methods and Evaluation Criteria in Supervised Learning
内容简介：The big data analytics relies on advanced data mining and machine learning methods. It is important to ensure correct use of these machine learning approaches for solving a variety of real-world problems. In this talk I will present several challenges and critical problems of applying supervised learning algorithms to classification and prediction. The talk will focus on feature engineering methods, imbalanced data handling techniques and propriate evaluation criteria in supervised learning.
报告人简介：Prof. Chaoyang Zhang‘s research includes data mining, machine learning, deep learning, big data analytics, image processing and pattern classification, bioinformatics, medical informatics. Prof. Zhang, as principal investigator or co-principal investigator, received eighteen research grants with a total of five million dollars, supported by US National Science Foundation, Department of Defense, National Institute of Health, Homeland Security, American Heart Association, etc. He has published more than eighty peer-reviewed journal articles and conference papers, one of which received the Sylvia Sorkin Greenfield Award (the best paper award of the Journal of Medical Physics, awarded by American Association of Physicists in Medicine in 2005). Prof. Zhang has been served on several National Science Foundation panels. He was the co-founder and Program Committee Chair of the International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing, (IJCBS’09) ShangHai, China, August 2009. He also severed as 2010 ACM-BCB Steering Committee Co-Chair, 2009 IJCBS conference program committee chair. Prof. Zhang was elected to serve as President of the US MCBIOS in 2014-2015 and he received MCBIOS Academic Service Award in 2018.