Investigating the Performance of a Novel Modified Binary Black Hole Optimization Algorithm for Enhancing Feature Selection

High-dimensional datasets often harbor redundant, irrelevant, and noisy features that detrimentally impact classification algorithm performance. Feature selection (FS) aims to mitigate this issue by identifying and retaining only the most pertinent features, thus reducing dataset dimensions. In this...

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Bibliographic Details

Published in:	Applied Sciences
Main Authors:	Mohammad Ryiad Al-Eiadeh, Raneem Qaddoura, Mustafa Abdallah
Format:	Article
Language:	English
Published:	MDPI AG 2024-06-01
Subjects:	feature selection wrapper feature selection black hole algorithm cuckoo search algorithm correlation functions transfer function
Online Access:	https://www.mdpi.com/2076-3417/14/12/5207