MMD-encouraging convolutional autoencoder: a novel classification algorithm for imbalanced data-Reference-Cited by-同舟云学术

MMD-encouraging convolutional autoencoder: a novel classification algorithm for imbalanced data

Published:2021-03-09 Issue:10 Volume:51 Page:7384-7401
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Li Bin,Gong Xiaofeng,Wang Chen,Wu Ruijuan,Bian Tong,Li Yanming,Wang Zhiyuan,Luo Ruisen^ORCID

Funder

Sichuan Science and Technology Program

University-Enterprise Cooperation Projects

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-02235-3.pdf

Reference44 articles.

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3. Minǎstireanu E, Meṡnitǎ G (2020) Methods of handling unbalanced datasets in credit card fraud detection. Brain 11:131–143

4. Liu S, Lin G, Han Q et al (2020) Deepbalance: Deep-learning and fuzzy oversampling for vulnerability detection. IEEE Trans Fuzzy Syst 28(7):1329–1343

5. Ren R, Yang Y, Sun L et al (2020) Oversampling technique based on fuzzy representativeness difference for classifying imbalanced data. Appl Intell 1–23

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