What are three possible ways to achieve this goal?

You are building a binary classification model by using a supplied training set.

The training set is imbalanced between two classes.

You need to resolve the data imbalance.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution NOTE: Each correct selection is worth one point.
A . Penalize the classification
B . Resample the data set using under sampling or oversampling
C . Generate synthetic samples in the minority class.
D . Use accuracy as the evaluation metric of the model.
E . Normalize the training feature set.

Answer: ABD

Explanation:

Explanation:

Reference: https://machinelearningmastery.com/tactics-to-combat-imbalanced-classes-in-your-machine-learning-dataset/