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Heterogeneous Drift Learning: Classification of Mix-Attribute Data with Concept Drifts

  • Published:2022-10-13 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)
  • language:
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Author:

Zhao Lang1,Zhang Yiqun1,Ji Yuzhu1,Zeng An1,Gu Fangqing2,Luo Xiaopeng3

Affiliation:

1. Guangdong University of Technology,School of Computer Science and Technology,Guangzhou,China

2. Guangdong University of Technology,School of Mathematics and Statistics,Guangzhou,China

3. BNU-HKBU United International College,Department of Computer Science,Zhuhai,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

IEEE

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning Hierarchical Representations in Temporal and Frequency Domains for Time Series Forecasting;Pattern Recognition and Computer Vision;2023-12-26

2. Unsupervised Concept Drift Detection via Imbalanced Cluster Discriminator Learning;Pattern Recognition and Computer Vision;2023-12-24

3. Selecting Heterogeneous Features Based on Unified Density-Guided Neighborhood Relation for Complex Biomedical Data Analysis;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

4. Review on novelty detection in the non-stationary environment;Knowledge and Information Systems;2023-11-30
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