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Hybrid metaheuristic approaches for feature selection in classification

Abstract

Feature selection plays a critical role in enhancing the performance of classification algorithms by identifying the most relevant features from datasets.

Traditional feature selection methods often struggle with the complexity of large datasets, where irrelevant or redundant features can degrade model accuracy and increase computational cost.

Metaheuristic algorithms are the most effective techniques for managing features. Recent studies have focused on using hybrid metaheuristics to solve feature selection problem due to their ability to explore large solution spaces efficiently.

Hybrid metaheuristic approaches, which combine the strengths of multiple optimization techniques are used to overcome problems of single metaheuristics such as premature convergence or insufficient exploration of the solution space.

Various hybrid metaheuristic algorithms for feature selection related to single and multi-objectives, balancing the exploration and exploitation of the solution space, improving the quality of selected feature subsets and performance metrics will be explored.

Short Biodata

Prof. Emerita Dr. Ku Ruhana holds a Bachelor's degree in Mathematical Sciences and a Master's degree in Computing, both received from Bradford University, United Kingdom, in 1983 and 1986, respectively. Her PhD in Computer Science was obtained from Universiti Pertanian Malaysia in 1994.

Prof. Dr. Ku Ruhana’s academic career began with her appointment as a teacher after receiving her Postgraduate Diploma in Teaching from Universiti Kebangsaan Malaysia in April 1984. She was later appointed as a Universiti Utara Malaysia (UUM) tutor and lecturer in August 1984 and January 1987, respectively, and as a professor in 2003.

Dr. Ku Ruhana has held several administrative posts at UUM. In 1994, she was appointed the Deputy Dean of the Faculty of Information Technology, and later became Director of the Centre for Innovations in Education in 1997. From 1998 until 2000, she led UUM’s Centre for Professional and Continuing Education.

In 2003, she was appointed as Dean for the Faculty of Information Technology, as Dean of the Centre for Graduate Studies in 2005, and as Dean for Academic Development in 2008. She returned as the Dean to Awang Had Salleh Graduate School in 2019.

Currently, she serves as a Professor Emerita in the Department of Computer Science, School of Computing, UUM. Additionally, she is an Adjunct Professor at Shibaura Institute of Technology, Japan, and Asia e-University, Malaysia. She also holds Visiting Professor positions at Universitas Islam Indragiri and Universitas Muhammadiyah Yogyakarta, Indonesia.

As an academic, her research interests include computer systems performance modelling, ant colony optimization, computational intelligence, and wireless sensor networks.

Her book on ‘C Programming’ won the Best Publication Award in the academic book category in 1999. In 2002, she published another academic book, ‘Mathematics for Business’. She served as the Chief Editor of the Journal of Information and Communication Technology for 21 years and as an associate editor for several other refereed journals.