Is providing class weight to neural network enough for imbalanced binary classification?

Question

I have a highly imbalanced binary classification problem, probably 95:5 for two classes. I don't want to perform resampling as the data is already huge and training it would just take more time. (I'm also aware of down sampling)
But my question is , is providing class weights (let's say computed by scikit-learn's compute class weight) enough?
or there is any other method ?
model.fit(X,y,class_weight=class_weight)

David Masip · Accepted Answer

Referring to an answer to a similar question, you don't have any reason to handle unbalance from the beginning. An imbalance of 95:5 isn't that big, I'd start with the regular training and if that doesn't work try more sophisticated things.

Correct answer by David Masip on September 13, 2020

Is providing class weight to neural network enough for imbalanced binary classification?

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