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Which techniques can be employed to reduce overfitting in machine learning models?
A
Data Augmentation (e.g., Image scaling, rotation to enhance training data)
B
Early Stopping (a method to halt training epochs to prevent overfitting)
C
Regularization (techniques aimed at reducing model complexity)
D
Dropout (a regularization technique to prevent overfitting by randomly ignoring neurons during training)
E
All of the above
