HHFS: A Hybrid Hierarchical Feature Selection Method for Ageing Gene Classification-Reference-Cited by-同舟云学术

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HHFS: A Hybrid Hierarchical Feature Selection Method for Ageing Gene Classification

Published:2022 Issue: Volume: Page:1-1
ISSN:2379-8920
Container-title:IEEE Transactions on Cognitive and Developmental Systems
language:
Short-container-title:IEEE Trans. Cogn. Dev. Syst.

Author:

Li Dehui¹,Wu Quanwang¹,Zhou Mengchu²,Luo Fengji³

Affiliation:

1. College of Computer Science, Chongqing University, Chongqing 400044, China.

2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA.

3. School of Engineering, the University of Sydney, Sydney, Australia.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Software

Link

http://xplorestaging.ieee.org/ielx7/7274989/7422051/09785518.pdf?arnumber=9785518

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1. Multi-strategy augmented Harris Hawks optimization for feature selection;Journal of Computational Design and Engineering;2024-03-22

2. A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection;IEEE/CAA Journal of Automatica Sinica;2024-02

3. Predicting the effect of genes on longevity with novel hierarchical dependency-constrained tree augmented naïve Bayes classifiers;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

4. Elucidating human ageing-related phenotypic abnormalities with a novel hierarchical feature selection-based knowledge discovery framework;2023-05-26

5. Modeling and Control of Robotic Manipulators Based on Artificial Neural Networks: A Review;Iranian Journal of Science and Technology, Transactions of Mechanical Engineering;2023-01-23

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