Tree‐Based Machine Learning Models for Predicting Phosphate Adsorption Performance of Layered Double Hydroxides: Insights Into Mechanisms and Process Optimization
Optimizing layered double hydroxides (LDHs) for phosphate removal is challenged by complex, multivariable interactions. To bridge this knowledge gap, this study introduces a novel data‐driven framework leveraging a comprehensive 2251‐record dataset and advanced machine learning to predict and optimize LDHs adsorption c...