HGSORF: Henry Gas Solubility Optimization-based Random Forest for C-Section prediction and XAI-based cause analysis

Md. Saiful Islam, Md. Abdul Awal, Jinnaton Nessa Laboni, Farhana Tazmim Pinki, Shatu Karmokar, Khondoker Mirazul Mumenin, Saad Al-Ahmadi, Md. Ashfikur Rahman, Md. Shahadat Hossain, Seyedali Mirjalili

Abstract: Highlights•A novel optimized ML classifier called HGSORF is proposed for CS prediction.•The HGSORF provides the highest accuracy of 98.33%.•Compared with other studies and frequently used optimization algorithms.•The XAI has been used to interpret the model and cause analysis.