会议论文

Wen, YM

英文

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

0302-9743

2020

12533 LNCS

639-650

27th International Conference on Neural Information Processing, ICONIP 2020

Lecture Notes in Computer Science

18 November 2020 through 22 November 2020

Bangkok, THAILAND

[Liu, Changjie;Wen, Yimin] Guilin Univ Elect Technol, Guangxi Key Lab Image & Graph Intelligent Proc, Guilin, Peoples R China.^[Xue, Yun] Hunan City Univ, Sch Municipal & Surveying Engn, Yiyang, Peoples R China.

Yang, H Pasupa, K Leung, ACS Kwok, JT Chan, JH King, I

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

Springer Science and Business Media Deutschland GmbH

9783030638320

10.1007/978-3-030-63833-7_54

Acknowledgments. This work was partially supported by the Natural Science Foundation of Guangxi District (2018GXNSFDA138006), National Natural Science Foundation of China (61866007, 61662014), Collaborative Innovation Center of Cloud Computing and Big Data (YD16E12) and Image Intelligent Processing Project of Key Laboratory Fund (GIIP201505).

本校为其他机构

In the real-world scenario of data stream classification, label scarcity is very common. More challenges are data streams always include concept drifts. To handle these challenges, an algorithm of semi-supervised classification of data streams based on adaptive density peak clustering (SSCADP) is proposed. In SSCADP, to generate concept clusters at leaves in a Hoeffding tree, a density peak clustering method and a change detection technique are combined to adaptively locate the clustering centers. Concerning concept drift detection, we argue th...