In a multi-class classification problem with class imbalance, all the options A, B, and C can be used to handle the issue. Resampling techniques can balance the class distribution, assigning different weights to the classes can help the model focus more on the minority class, and a weighted voting scheme can give more importance to the minority class in the final prediction. Class imbalance can lead to biased predictions, where the ensemble model may favor the majority class, thus affecting the overall performance. Therefore, the correct answer is D, as all the options can be used to address class imbalance in the ensemble.