@inproceedings{27a057c2d2034a359f4debb6ca831e32,
title = "Keep it simple: random oversampling for imbalanced data",
abstract = "The issue of imbalanced data affects a wide range of applications. Despite a plethora of sophisticated sampling techniques for dealing with imbalanced data, the simple random oversampling (ROS) method remains a robust alternative. The goal of this paper is to compare the performance of ROS to the more advanced sampling algorithms. To this end, we conduct numerical experiments on multi-label data. The results of the experiments reveal that ROS outperforms several advanced sampling algorithms. Given the computational efficiency of ROS and its robust accuracy, we believe that it provides a good option for dealing with imbalanced data.",
keywords = "data mining, imbalanced data, machine learning, random oversampling",
author = "Firuz Kamalov and Leung, {Ho Hon} and Cherukuri, {Aswani Kumar}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Advances in Science and Engineering Technology International Conferences, ASET 2023 ; Conference date: 20-02-2023 Through 23-02-2023",
year = "2023",
doi = "10.1109/ASET56582.2023.10180891",
language = "English",
series = "2023 Advances in Science and Engineering Technology International Conferences, ASET 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 Advances in Science and Engineering Technology International Conferences, ASET 2023",
}