Parsimonious random vector functional link network for data streams

• Main Authors: Pratama, Mahardhika, Angelov, Plamen P., Lughofer, Edwin, Er, Meng Joo
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: Random Vector Functional Link; Evolving Intelligent System
• Online Access: https://hdl.handle.net/10356/89370; http://hdl.handle.net/10220/44904
• Institution: Nanyang Technological University

The majority of the existing work on random vector functional link networks (RVFLNs) is not scalable for data stream analytics because they work under a batch learning scenario and lack a self-organizing property. A novel RVLFN, namely the parsimonious random vector functional link network (pRVFLN),...