A stacking ensemble of standard classifiers with SMOTE achieves 96% test accuracy on 3-class earthquake damage grade prediction from building attributes.
Scalable decision trees for earthquake damage assessment
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Earthquake Damage Grades Prediction using An Ensemble Approach Integrating Advanced Machine and Deep Learning Models
A stacking ensemble of standard classifiers with SMOTE achieves 96% test accuracy on 3-class earthquake damage grade prediction from building attributes.