Toward feature selection in big data preprocessing based on hybrid cloud-based model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-021-03970-7.pdf
Reference48 articles.
1. García-Gil D, Luengo J, García S, Herrera F (2019) Enabling smart data: noise filtering in big data classification. Inf Sci 479:135–152
2. Zheng W, Zhu X, Wen G, Zhu Y, Yu H, Gan J (2020) Unsupervised feature selection by self-paced learning regularization. Pattern Recogni Lett 132:4–11
3. Mohamad M, Selamat A, Krejcar O, Fujita H, Wu T (2020) An analysis on new hybrid parameter selection model performance over big data set. Knowl-Based Syst 192:105441
4. V. Kumar, A. Verma, N. Mittal, S. V. Gromov, (2019) Anatomy of preprocessing of big data for monolingual corpora paraphrase extraction: source language sentence selection. In: Emerging Technologies in Data Mining and Information Security, Springer, pp. 495–505
5. A. Sinha, B. Sahoo, S. S. Rautaray, M. Pandey, (2020) Predictive model prototype for the diagnosis of breast cancer using big data technology. In: Advances in Data and Information Sciences, Springer, pp. 455–464
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Application of Preprocessing Techniques on the Dataset obtained from Education Sector to Predict Students’ Performance;2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon);2024-04-25
2. A Case Study of Big Data Processing in the Cloud Environments with Insights into Advantages, Tools, and Techniques;2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence);2024-01-18
3. Investigating Machine Learning Techniques Used for the Detection of Class Noise in Data: A Systematic Literature Review;Lecture Notes in Networks and Systems;2024
4. A novel similarity measurement for triangular cloud models based on dual consideration of shape and distance;PeerJ Computer Science;2023-08-09
5. Preprocessing Big Data using Partitioning Method for Efficient Analysis;2023 IEEE International Conference on Contemporary Computing and Communications (InC4);2023-04-21
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3