A Comprehensive Survey on the Process, Methods, Evaluation, and Challenges of Feature Selection-Reference-Cited by-同舟云学术

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A Comprehensive Survey on the Process, Methods, Evaluation, and Challenges of Feature Selection

Published:2022 Issue: Volume:10 Page:99595-99632
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Islam Md Rashedul¹^ORCID,Lima Aklima Akter²^ORCID,Das Sujoy Chandra²^ORCID,Mridha M. F.²^ORCID,Prodeep Akibur Rahman²^ORCID,Watanobe Yutaka³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh

2. Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh

3. Department of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09885186.pdf?arnumber=9885186

Cited by 24 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. Neural network prediction of thermal field spatiotemporal evolution during additive manufacturing: an overview;The International Journal of Advanced Manufacturing Technology;2024-08-20

2. An Improved Binary Walrus Optimizer with Golden Sine Disturbance and Population Regeneration Mechanism to Solve Feature Selection Problems;Biomimetics;2024-08-18

3. Dynamic target feature selection in pixel change space for array GM-APD lidar;Infrared Physics & Technology;2024-08

4. Improving Performance With Feature Selection, Extraction, and Learning;Integrating Metaheuristics in Computer Vision for Real‐World Optimization Problems;2024-07-31

5. Inversion of Forest Aboveground Biomass in Regions with Complex Terrain Based on PolSAR Data and a Machine Learning Model: Radiometric Terrain Correction Assessment;Remote Sensing;2024-06-19

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