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Ah, yes, good point. So the weight would be for the task, not the class label. Class 0 would still be weighted in a sense, since if you consider it as p(y > 0), the answer is Yes or No. So, the task weight here affects both class 0 and class 1. |
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I was wondering if that's a good way of calculating importance weights for the tasks:
What do you guys think? |
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First of all, thank you so much for your work!
I am trying to use the coral loss function with an unbalanced dataset. Then, I suppose weight importance is for that however the input data have to be sized n_classes -1. I suppose class 0 can not be weighted. Am I right?
However, class 0 is the smallest one! Do you have some suggestions?
Thank you so much!
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