A new data complexity measure for multi-class imbalanced classification tasks-Reference-Cited by-同舟云学术

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A new data complexity measure for multi-class imbalanced classification tasks

Published:2025-01 Issue: Volume:157 Page:110881
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Han Mingming,Guo Husheng,Wang Wenjian

Funder

Shanxi Provincial Key Research and Development Project

National Aerospace Science Foundation of China

International Science and Technology Cooperation Program of Shanxi Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference34 articles.

1. To combat multi-class imbalanced problems by means of over-sampling techniques;Abdi;IEEE Trans. Knowl. Data Eng.,2015

2. Noise-robust oversampling for imbalanced data classification;Liu;Pattern Recognit.,2023

3. Addressing the class-imbalance and class-overlap problems by a metaheuristic-based under-sampling approach;Soltanzadeh;Pattern Recognit.,2023

4. Assessing the data complexity of imbalanced datasets;Barella;Inform. Sci.,2021

5. Classifier calibration: a survey on how to assess and improve predicted class probabilities;Silva Filho;Mach. Learn.,2023

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