An interpretable neural fuzzy inference system for predictions of underpricing in initial public offerings

• Main Authors: Qian, Xiaolin, Quek, Chai, Miao, Chunyan, Wang, Di, Zhang, Xiaofeng, Ng, Geok See, Zhou, You, Tan, Ah-Hwee
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Computer science and engineering; Neural Fuzzy Inference System; Interpretable Rules
• Online Access: https://hdl.handle.net/10356/80561; http://hdl.handle.net/10220/46696
• Institution: Nanyang Technological University

Due to their aptitude in both accurate data processing and human comprehensible reasoning, neural fuzzy inference systems have been widely adopted in various application domains as decision support systems. Especially in real-world scenarios such as decision making in financial transactions, the hum...