一、时间
2024年10月20日（周日）下午15:30
二、地点
学术会议中心201
叁、主要内容
报告主题：Explainable Classifier Design with Reject Options and its Extensions
报告内容：In recent years, machine learning (ML) models have been increasingly applied to fields such as medicine and finance. However, these fields require additional trust in the model's outputs. For this reason, ML models should have high explainability and reliability in their classification as an additional requirement to the usual high classification accuracy. Fuzzy classifiers with a reject option are promising for the above issue thanks to the linguistic explainability of fuzzy if-then rules and the reliable outputs using a reject option. This talk introduces three recent achievements related to fuzzy classifiers with a reject option. One is the accuracy improvement using a second opinion by a different ML model. Another is a hierarchical classifier design considering feature costs. The other is a partially explainable model using white- and black-box ML models.
四、主讲嘉宾
Professor Yusuke Nojima received the B.S. and M.S. Degrees in Mechanical Engineering from Osaka Institute of Technology, Osaka, Japan, in 1999 and 2001, respectively, and the Ph.D. degree from the Department of System Function Science from Kobe University, Hyogo, Japan, in 2004. Since 2004, he has been with Osaka Prefecture University, Osaka, Japan, where he was a Professor in the Department of Computer Science and Intelligent Systems from October 2020. From April 2022, he has been a Professor in the Department of Core Informatics, Graduate School of Informatics, Osaka Metropolitan University, Osaka, Japan. His research interests include evolutionary fuzzy systems, evolutionary multiobjective optimization, and multiobjective data mining. He co-authored more than 300 papers in journals and international conferences. His papers have been cited more than 10,000 times so far, and his H-index in Google Scholar is 47 (Oct. 18, 2024). He received the Best Paper Awards from various international conferences and IEEE Transactions like HIS 2006, FUZZ-IEEE 2009, WAC 2010, FUZZ-IEEE 2011, ACIIDS 2015, GECCO 2017, EMO 2019, IFSA 2023, and IEEE TEVC 2017. For more details, please visit https://yusuke-nojima.github.io