Parsimonious random vector functional link network for data streams
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),...
Main Authors: | Pratama, Mahardhika, Angelov, Plamen P., Lughofer, Edwin, Er, Meng Joo |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/89370 http://hdl.handle.net/10220/44904 |
Similar Items
-
Evolving ensemble fuzzy classifier
by: Pratama, Mahardhika, et al.
Published: (2019) -
Online dynamic ensemble deep random vector functional link neural network for forecasting
by: Gao, Ruobin, et al.
Published: (2024) -
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
by: Li, Ruilin, et al.
Published: (2024) -
Automatic online multi-source domain adaptation
by: Xie, Renchunzi, et al.
Published: (2022) -
Online identification of a rotary wing Unmanned Aerial Vehicle from data streams
by: Ferdaus, Md Meftahul, et al.
Published: (2021)