Leveraging the trade-off between accuracy and interpretability in a hybrid intelligent system

• Main Authors: Miao, Chunyan, Zhou, You, Wang, Di, Quek, Chai, Tan, Ah-Hwee, Ng, Geok See
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Computer science and engineering; Neural Fuzzy Inference System; Interpretability
• Online Access: https://hdl.handle.net/10356/89595; http://hdl.handle.net/10220/47060
• Institution: Nanyang Technological University

Neural Fuzzy Inference System (NFIS) is a widely adopted paradigm to develop a data-driven learning system. This hybrid system has been widely adopted due to its accurate reasoning procedure and comprehensible inference rules. Although most NFISs primarily focus on accuracy, we have observed an ever...