Dealing with class imbalance in classifier chains via random undersampling-Reference-Cited by-同舟云学术

Dealing with class imbalance in classifier chains via random undersampling

Published:2020-03 Issue: Volume:192 Page:105292
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liu Bin,Tsoumakas Grigorios

Funder

China Scholarship Council

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference39 articles.

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4. Classification and Regression Trees;Breiman,1984

5. B. Liu, G. Tsoumakas, Making classifier chains resilient to class imbalance, in: 10th Asian Conference on Machine Learning (ACML 2018), Beijing, 2018, pp. 280–295.

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