A stacking ensemble of standard classifiers with SMOTE achieves 96% test accuracy on 3-class earthquake damage grade prediction from building attributes.
Testing machine learning models for seismic damage prediction at a regional scale using building-damage dataset compiled after the 2015 gorkha nepal earthquake
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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.