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Han M, Li X, Wang L, Zhang N, Cheng H. Review of ensemble classification over data streams based on supervised and semi-supervised. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022. [DOI: 10.3233/jifs-211101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Most data stream ensemble classification algorithms use supervised learning. This method needs to use a large number of labeled data to train the classifier, and the cost of obtaining labeled data is very high. Therefore, the semi supervised learning algorithm using labeled data and unlabeled data to train the classifier becomes more and more popular. This article is the first to review data stream ensemble classification methods from the perspectives of supervised learning and semi-supervised learning. Firstly, basic classifiers such as decision trees, neural networks, and support vector machines are introduced from the perspective of supervised learning and semi-supervised learning. Secondly, the key technologies in data stream ensemble classification are explained from the two aspects of incremental and online. Finally, the majority voting and weight voting are explained in the ensemble strategies. The different ensemble methods are summarized and the classic algorithms are quantitatively analyzed. Further research directions are given, including the handling of concept drift under supervised and semi-supervised learning, the study of homogeneous ensemble and heterogeneous ensemble, and the classification of data stream ensemble under unsupervised learning.
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Affiliation(s)
- Meng Han
- School of Computer Science and Engineering, North Minzu University, Yinchuan, China
| | - Xiaojuan Li
- School of Computer Science and Engineering, North Minzu University, Yinchuan, China
| | - Le Wang
- School of Computer Science and Engineering, North Minzu University, Yinchuan, China
| | - Ni Zhang
- School of Computer Science and Engineering, North Minzu University, Yinchuan, China
| | - Haodong Cheng
- School of Computer Science and Engineering, North Minzu University, Yinchuan, China
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