Online feature selection for multi-source streaming features

Author:

You Dianlong,Sun Miaomiao,Liang Shunpan,Li Ruiqi,Wang Yang,Xiao Jiawei,Yuan Fuyong,Shen Limin,Wu Xindong

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference49 articles.

1. Toward mining capricious data streams: A generative approach;He;IEEE Trans. Neural Networks Learn. Syst.,2020

2. Y. He, X. Yuan, S. Chen, X. Wu, Online learning in variable feature spaces under incomplete supervision, in: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, 2021, pp. 4106–4114.

3. Online feature selection with capricious streaming features: A general framework, in;Wu;IEEE International Conference on Big Data (Big Data),2019

4. Y. He, B. Wu, D. Wu, X. Wu, On partial multi-task learning, in: the 24th European Conference on Artificial Intelligence, IOS Press, 2020, pp. 1174–1181.

5. Heterogeneous ensemble selection for evolving data streams;Luong;Pattern Recogn.,2021

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