Chee Keong Lee

Machine Learning in Biomass Valorization for Energy and Fuels: A Review and Perspectives on Feature Representation and Process Decision-Making

The reviewed literature shows that hybrid feedstock-process descriptors often improve predictive performance because they represent both biomass identity and conversion environment, but they also increase the risks of overfitting, inconsistent reporting, multicollinearity, and leakage when feature timing is unclear.