A Review of Genetic Algorithms for Feature Selection in Machine Learning
Abstract
This review paper discusses how Genetic Algorithms are used for feature selection in machine learning classification problems. It examines recent research studies and explains how GA helps reduce the number of features while improving model performance. The paper also compares different approaches, highlights practical applications such as medical diagnosis and network security, and discusses current challenges and future research directions.
Fields of Study & Subjects
Evolutionary Algorithms and Applications
Metaheuristic Optimization Algorithms Research
Text and Document Classification Technologies
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 January 2026
- Language
- EN