2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)最新文献

筛选
英文 中文
Comparison of Controlled Undersampling Methods for Machine Learning 机器学习的受控欠采样方法比较
Jiříy Setinský, Martin Žádník
{"title":"Comparison of Controlled Undersampling Methods for Machine Learning","authors":"Jiříy Setinský, Martin Žádník","doi":"10.1109/ACDSA59508.2024.10467755","DOIUrl":"https://doi.org/10.1109/ACDSA59508.2024.10467755","url":null,"abstract":"Data reduction is an important preprocessing operation for Machine Learning to learn from large datasets, especially in the case of applications requiring online learning using constrained resources. Our survey focuses on a specific family of data reduction methods - controlled undersampling methods. We observe the behaviour of the methods as they cooperate with several supervised machine-learning techniques over multiple evaluation datasets. Our results show that the random undersampling method offers surprisingly good results compared to more complex methods and is a good fit for online and resource-sensitive machine-learning applications.","PeriodicalId":518964,"journal":{"name":"2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)","volume":"55 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140528970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信