An Incremental Approach to Recursive Genetic Algorithm Learning with Automatic Data Decomposition
A recursive domain decomposition approach combined with task decomposition is proposed to tackle the difficulty of classification problems caused by the complex pattern relationship and curse of dimensionality. An incremental hyperplane partitioning approach is proposed for classification. Hyperplanes that are close to the classification boundaries of a given problem are searched using an incremental approach based upon Genetic Algorithm (GA). A new method - Incremental Linear Encoding based Genetic Algorithm (ILEGA) is proposed for that purpose. We solve classification problems through a simple and flexible chromosome encoding scheme, where the partitioning rules are encoded by linear equations rather than If-Then rules. The algorithm is tested with six datasets. The experimental results show that ILEGA outperform in both lower- and higher-dimensional problems compared with the original GA. A variation of the incremental hyperplane partitioning approach is also presented, namely incremental hypersphere partitioning.
Prof. Steven Sheng-Uei Guan
Date & Time
2 Sep 2016 (Friday) 11:30 - 12:30
E11-1025 (University of Macau)
Department of Computer and Information Science
Steven Guan received his M.Sc. & Ph.D. from the University of North Carolina at Chapel Hill. He is currently a Professor and the Director for Research Institute of Big Data Analytics at Xi'an Jiaotong-Liverpool University (XJTLU). He served the head of department position at XJTLU for 4.5 years, creating the department from scratch and now in shape. Before joining XJTLU, he was a tenured professor and chair in intelligent systems at Brunel University, UK.
Prof. Guan has worked in a prestigious R&D organization for several years, serving as a design engineer, project leader, and department manager. After leaving the industry, he joined Yuan-Ze University in Taiwan for three and half years. He served as deputy director for the Computing Center and the chairman for the Department of Information & Communication Technology. Later he joined the Electrical & Computer Engineering Department at National University of Singapore as an associate professor. Prof. Guan’s research interests include: machine learning, big data analytics, modeling, security, networking, mobile commerce, and pseudorandom number generation. He has published extensively in these areas, with 130+ journal papers and 180+ book chapters or conference papers. He has chaired and delivered keynote speeches for 30+ international conferences and served in 170+ international conference committees and 20+ editorial boards.