Detecting Non-injured Passengers and Drivers in Car Accidents: A New Under-resampling Method for Imbalanced Classification
imbalanced data; resampling; under-sampling; classification; random forest; rare event detection; imbalance learning
Advances in Business and Management Forecasting, Volume 13
We then propose a new procedure to resample the data. Our method is based on the idea of eliminating “easy” majority observations before under-sampling them. It has further improved the balanced accuracy of the Random Forest to 83.7%, making it the best approach for the imbalanced data.