MOBCSA: Multi-Objective Binary Cuckoo Search Algorithm for Features Selection in Bioinformatics

MOBCSA: Multi-Objective Binary Cuckoo Search Algorithm for Features Selection in Bioinformatics

In bioinformatics, medical diagnosis models might be significantly impacted by high-dimensional data generated by high-throughput technologies. This data includes redundant or irrelevant genes, making it challenging to identify the relevant genes from such high-dimensional data. Therefore, an effect...

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Bibliographic Details
Main Authors: Hudhaifa Mohammed Abdulwahab, S. Ajitha, Mufeed Ahmed Naji Saif, Belal Abdullah Hezam Murshed, Fahd A. Ghanem
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Features selection
multi-objective optimization
cuckoo search algorithm
machine learning
data mining
bioinformatics
Online Access:https://ieeexplore.ieee.org/document/10419347/

Internet

https://ieeexplore.ieee.org/document/10419347/

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