A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Machine learning algorithms show promise for the detection of current frailty status, particularly in binary classification. However, distinguishing between frailty subcategories remains challenging, highlighting the need for improved models and feature selection strategies to enhance multi-class classification accuracy.