Hello !
I’d like to try my hand at Deep Learning for Tabular Data. Except my two classes are hugely imbalanced.
Like one class is 99% of the dataset, and the other one is 1%…
So I tried to run the classroom notebook with the ADULTS dataset, and change the metric (because accuracy is not a good idea for imbalance: it will just learn to always predict the 99% class).
I tried to change accuracy to fbeta, and got the following error:
RuntimeError: The size of tensor a (2) must match the size of tensor b (64) at non-singleton dimension 1
Two questions:
-> should I use fbeta as a metric, or use another approach ?
-> if I should use fbeta, what’s wrong with the above code ?
Thank you very much and have a nice day !