Classification of Breast Cancer on the Strength of Potential Risk Factors with Boosting Models: A Public Health Informatics Application
Aim:The diagnosis of breast cancer can be accomplished using an algorithm or an early detection model of breast cancer risk via determining factors.In the present study, gradient boosting machines (GBM), extreme gradient boosting (XGBoost) and light gradient boosting (LightGBM) models were applied Shade and their performances were compared.Methods: