Prediction Models for Individuals' Control Skill Development and Retention using XGBoost and SHAP

Current capabilities for predicting skill retention, i.e., the extent to which human operators retain learned skills over time, at an individual level are limited due to a requirement for large data sets and methods that can extract relevant patterns in highly dimensional data. This paper investigates the application of Extreme Gradient Boosting...