A new two-stage hybrid feature selection algorithm and its application in Chinese medicine-Reference-Cited by-同舟云学术

A new two-stage hybrid feature selection algorithm and its application in Chinese medicine

Published:2021-11-01 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Li Zhiqin,Du Jianqiang^ORCID,Nie Bin,Xiong Wangping,Xu Guoliang,Luo Jigen

Funder

natural science foundation of jiangxi province

National Natural Science Foundation of China

National Key R&D Program of China

Key Research and Development Program of Jiangxi Province

Technology Research Project of Jiangxi Provincial Department of Education

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-021-01445-y.pdf

Reference37 articles.

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3. Ferdinando DM, Sabrina S (2020) Balancing the user-driven feature selection and their incidence in the clustering structure formation. Appl Soft Comput 98:106854

4. Al-Rimy BAS, Maarof MA, Shaid SZM et al (2021) Redundancy coefficient gradual up-weighting-based mutual information feature selection technique for crypto-ransomware early detection. Fut Gener Comput Syst 115:641–658

5. Rostami O, Kaveh M (2021) Optimal feature selection for SAR image classification using biogeography-based optimization (BBO), artificial bee colony (ABC) and support vector machine (SVM): a combined approach of optimization and machine learning. Comput Geosci. https://doi.org/10.1007/s10596-020-10030-1

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