Breast cancer prediction with feature-selected XGB classifier, optimized by metaheuristic algorithms

• Published in: Journal of big data Vol. 12; no. 1; pp. 78 - 26
• Main Authors: Sarker, Proshenjit, Ksibi, Amel, Jamjoom, Mona M., Choi, Kwonhue, Nahid, Abdullah Al, Samad, Md Abdus
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2025; Springer Nature B.V; SpringerOpen
• Subjects: Accuracy; Algorithms; Bald eagle search; Big Data; Breast cancer; Communications Engineering; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Database Management; Datasets; Glucose; Heuristic methods; Information Storage and Retrieval; Mathematical Applications in Computer Science; Metaheuristic algorithms; Networks; Optimization; Uncontrolled; Whale optimization; Wrapper model; Whale optimization; SHAP; Sea lion optimization; Wrapper model; Extreme gradient boost; Uncontrolled; Breast cancer; Bald eagle search; Metaheuristic algorithms

Breast cancer, caused by uncontrolled cell growth in milk ducts or lobules, has the highest mortality rate among women worldwide, with Asia reporting the most deaths. Early detection improves survival rates and reduces treatment costs. This study aims to develop a feature selection-based classifier...