A hybrid multi-objective genetic algorithm for gene selection in microarray data-Reference-Cited by-同舟云学术

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A hybrid multi-objective genetic algorithm for gene selection in microarray data

Published:2023-10-20 Issue: Volume:2015 Page:443-449
ISSN:
Container-title:Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science
language:
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Author:

Su Yizhou¹^ORCID,Zhao Guohua²^ORCID,Lin Yusong³^ORCID

Affiliation:

1. School of Computer and Artificial Intelligence, Zhengzhou University, China

2. Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China

3. School of Cyber Science and Engineering, Zhengzhou University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3644116.3644190

Reference13 articles.

1. Approaches, Applications, and Challenges[J];Jiao R;IEEE Transactions on Evolutionary Computation,2023

2. Mining gene expression data using data mining techniques: A critical review

3. Ben-Dor A Bruhn L Friedman N Tissue classification with gene expression profiles[C]//Proceedings of the fourth annual international conference on Computational molecular biology. 2000: 54-64.

4. Deb K, Jain H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints[J]. IEEE transactions on evolutionary computation, 2013, 18(4): 577-601.

5. A problem-specific non-dominated sorting genetic algorithm for supervised feature selection

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