GOG-MBSHO: multi-strategy fusion binary sea-horse optimizer with Gaussian transfer function for feature selection of cancer gene expression data

Wang, Yu-Cai; Song, Hao-Ming; Wang, Jie-Sheng; Song, Yu-Wei; Qi, Yu-Liang; Ma, Xin-Ru

doi:10.1007/s10462-024-10954-5

Artif Intell Rev

2024

DOI: 10.1007/s10462-024-10954-5

|View full text |Cite

GOG-MBSHO: multi-strategy fusion binary sea-horse optimizer with Gaussian transfer function for feature selection of cancer gene expression data

Yu-Cai Wang,

Hao-Ming Song,

Jie-Sheng Wang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

An improved conditional relevance and weighted redundancy feature selection method for gene expression data

Qin,

Zhang,

Dong

et al. 2024

J Supercomput

View full text Add to dashboard Cite

An improved conditional relevance and weighted redundancy feature selection method for gene expression data

Qin,

Zhang,

Dong

et al. 2024

J Supercomput

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

GOG-MBSHO: multi-strategy fusion binary sea-horse optimizer with Gaussian transfer function for feature selection of cancer gene expression data

Cited by 1 publication

References 74 publications

An improved conditional relevance and weighted redundancy feature selection method for gene expression data

An improved conditional relevance and weighted redundancy feature selection method for gene expression data

Contact Info

Product

Resources

About