Imbalanced data preprocessing techniques for machine learning: a systematic mapping study
V Werner de Vargas, JA Schneider Aranda… - … and Information Systems, 2023 - Springer
Abstract Machine Learning (ML) algorithms have been increasingly replacing people in
several application domains—in which the majority suffer from data imbalance. In order to …
several application domains—in which the majority suffer from data imbalance. In order to …
A review of machine learning techniques in Imbalanced Data and Future trends
E Jafarigol, T Trafalis - arXiv preprint arXiv:2310.07917, 2023 - arxiv.org
For over two decades, detecting rare events has been a challenging task among
researchers in the data mining and machine learning domain. Real-life problems inspire …
researchers in the data mining and machine learning domain. Real-life problems inspire …
Imbalance in learning chest X-ray images for COVID-19 detection
We present a method which enables to learn and recognize symptoms of COVID-19 from
chest X-ray images in a class balancing algorithm. Images are trained and tested by deep …
chest X-ray images in a class balancing algorithm. Images are trained and tested by deep …
[PDF][PDF] CDR2IMG: A Bridge from Text to Image in Telecommunication Fraud Detection.
Z Zhen, J Gao - Comput. Syst. Sci. Eng., 2023 - cdn.techscience.cn
Telecommunication fraud has run rampant recently worldwide. However, previous studies
depend highly on expert knowledge-based feature engineering to extract behavior …
depend highly on expert knowledge-based feature engineering to extract behavior …