Binary classification for imbalanced datasets using twin hyperspheres based on conformal method-Reference-Cited by-同舟云学术

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Binary classification for imbalanced datasets using twin hyperspheres based on conformal method

Published:2024-05-22 Issue:8 Volume:27 Page:11299-11315
ISSN:1386-7857
Container-title:Cluster Computing
language:en
Short-container-title:Cluster Comput

Author:

Zheng Jian,Li Lin,Wang Shiyan,Yan Huyong

Funder

Science and Technology Research Program of Chongqing Municipal Education Commission of China

Natural Science Foundation of Chongqing

the National Social Science Fund Project of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10586-024-04528-x.pdf

Reference43 articles.

1. Mallikarjuna, C., Sivanesan, S.: Question classification using limited labeled data. Inf. Process. Manage. 59(6), 1–15 (2022)

2. Tang, Bo., He, H.: GIR-based ensemble sampling approaches for imbalanced learning. Pattern Recogn. 71, 306–319 (2017)

3. Furundzic, D., Stankovic, S., Jovicic, S.T., Punišić, S., Subotić, M.: Distance based resampling of imbalanced classes: With an application example of speech quality assessment. Eng. Appl. Artif. Intell. 64, 440–461 (2017)

4. Feng, L., Wang, H., Jinl, B.: Learning a distance Metric by balancing KL-divergence for imbalanced datasets. IEEE transaction on Systems, Man, and Cybernetics: Systems 49(12), 2384–2395 (2019)

5. Ando, S., Huang, C.Y.: Deep over-sampling framework for classifying imbalanced data. Proc. Joint Eur. Conf. Mach. Learn. Knowl. Discovery Databases, 770–785 (2017).

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