Relevant information undersampling to support imbalanced data classification-Reference-Cited by-同舟云学术

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Relevant information undersampling to support imbalanced data classification

Published:2021-05 Issue: Volume:436 Page:136-146
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Hoyos-Osorio J.,Alvarez-Meza A.,Daza-Santacoloma G.,Orozco-Gutierrez A.,Castellanos-Dominguez G.

Funder

Universidad Tecnológica de Pereira

Departamento Administrativo de Ciencia, Tecnología e Innovación

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference31 articles.

1. X. Guo, Y. Yin, C. Dong, G. Yang, G. Zhou, On the class imbalance problem, in: 2008 Fourth International Conference on Natural Computation, vol. 4, IEEE, 2008, pp. 192–201.

2. A comprehensive data level analysis for cancer diagnosis on imbalanced data;Fotouhi;J. Biomed. Inf.,2019

3. Deep class-skewed learning for face recognition;Wang;Neurocomputing,2019

4. R. Jhangiani, D. Bein, A. Verma, Machine learning pipeline for fraud detection and prevention in e-commerce transactions, in: 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), IEEE, 2019, pp. 0135–0140.

5. Cost-sensitive support vector machines;Iranmehr;Neurocomputing,2019

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3. Methods for class-imbalanced learning with support vector machines: a review and an empirical evaluation;Soft Computing;2024-07-25

4. A novel undersampling method based on data classification method;Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi;2024-07-15

5. Undersampling based on generalized learning vector quantization and natural nearest neighbors for imbalanced data;International Journal of Machine Learning and Cybernetics;2024-07-03

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