APA (7th ed.) Citation

Nicho, M., Hamed, A., Gaber, T., & Arimi, J. H. A. A-XGBoost: A resilient machine learning technique for predicting crimes against women across cultures on low cardinality crime data. Taylor & Francis Group.

Chicago Style (17th ed.) Citation

Nicho, Mathew, Ahmed Hamed, Tarek Gaber, and Jamal Hamad Al Arimi. A-XGBoost: A Resilient Machine Learning Technique for Predicting Crimes Against Women Across Cultures on Low Cardinality Crime Data. Taylor & Francis Group.

MLA (9th ed.) Citation

Nicho, Mathew, et al. A-XGBoost: A Resilient Machine Learning Technique for Predicting Crimes Against Women Across Cultures on Low Cardinality Crime Data. Taylor & Francis Group.