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

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)