Hybrid Nature-Inspired Based Oversampling and Feature Selection Approach for Imbalance Data Streams Classification-Reference-Cited by-同舟云学术

Hybrid Nature-Inspired Based Oversampling and Feature Selection Approach for Imbalance Data Streams Classification

Published:2023-02-08 Issue: Volume: Page:
ISSN:
Container-title:2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)
language:
Short-container-title:

Author:

Arya Monika¹,Dewangan Bhupesh Kumar²,Verma Monika³,Rohini M.⁴,Motwani Anand⁵,Sar Sumit Kumar³

Affiliation:

1. Bhilai Institute of Technology,Dept. Of Computer Science & Engineering,Durg CG,India

2. OP Jindal University,Dept. of computer Science Engineering,Raigarh,India

3. Bhilai Institute of Technology,Dept. of computer Science & Engineering,Durg,India

4. Sri Krishna College of Engineering and Technology,Dept. of computer Science & Engineering,Coimbatore,India

5. VIT Bhopal University,School of Computing Science & Engineering,Sehore MP,India

Publisher

IEEE

Link

Reference19 articles.

4. Ensemble deep learning approach with attention mechanism for COVID-19 detection and prediction;arya;Smart Innovation Systems and Technologies,2022

Cited by 2 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. ML-Based Feature Selection Technique for Imbalanced Data Streams;2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT);2023-10-26

2. An Adaptive Streaming Feature Selection Technique for Classifying Non-Stationary Data Streams;2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT);2023-10-26