XGB-COF: A machine learning software in Python for predicting the friction coefficient of porous Al-based composites with Extreme Gradient Boosting

This paper presents a software called XGB-COF that uses machine learning algorithm Extreme Gradient Boosting to predict the coefficient of friction (COF) porous AlSi10Mg-Al2O3 composites, tested by pin-on-disk method under dry sliding conditions. The is based on python and various packages for data processing, learning, visualization. aims address research challenge developing enhancing materials with improved wear resistance low different engineering domains. performs hyperparameter tuning using GridSearchCV training validation sets find optimal values rate number estimators. It assesses model’s performance test set determination, squared error, root mean absolute error. also generates stores plot actual vs predicted COF over time, metrics, both sets. available at https://codeocean.com/capsule/7130568/tree/v1 an MIT license.