Dr. MengChu ZhouNew Jersey Institute of Technology
Big data research has been receiving numerous attentions from industry and academia due to its vast application potential in business, manufacturing, health-care, and government agencies since over ten years ago when Google initiated the MapReduce project. Some new data-intensive and interesting research fields and problems have emerged. Class imbalance problems become the greatest issue in big data mining because of the unbounded size and imbalance nature of datasets. Under-sampling is a popular data preprocessing method in dealing with class imbalance problems with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority samples. It always uses full minority data in a training dataset. However, some noisy minority examples may reduce the performance of classifiers. In this talk, a new under-sampling scheme is given by incorporating a noise filter before executing resampling. In order to verify the efficiency, this scheme is implemented based on four popular under-sampling methods. Experimental results indicate that the proposed scheme can improve the original undersampling-based methods with significance in terms of the popular metrics for imbalanced classification.
MengChu Zhou received his B.S. degree in Control Engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, M.S. degree in Automatic Control from Beijing Institute of Technology, Beijing, China in 1986, and Ph. D. degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, NY in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests are in Petri nets, Internet of Things, big data, web services, manufacturing, transportation, and energy systems. He has over 700 publications including 12 books, 390+ journal papers (280+ in IEEE Transactions), 11 patents, and 28 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering. He is a recipient of Humboldt Research Award for US Senior Scientists from Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society. He has been among most highly cited scholars for years and ranked top one in the field of engineering worldwide in 2012 by Web of Science/Thomson Reuters. His Google citation count is well over 23, 000 and H-index is 75. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of IEEE, International Federation of Automatic Control (IFAC) and American Association for the Advancement of Science (AAAS).
Host: Dr. Houshang Darabi
For more information, please contact Prof. Houshang Darabi.