Urban waterlogging susceptibility assessment based on feature selection optimization and interpretable machine learning
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Flood susceptibility studies that utilize machine learning (ML) face challenges in interpretability and generalization due to the disconnection between feature selection and model training. This study proposed the C2MI-ML framework, which integrates the Chi-sq... ...
