I had a few quick questions on the tabular learner. I have a dataset where target is 0 and 1, but for some reasons tabular learner defines the loss as cross entropy and not log loss or some other function which makes more sense for binary classification. Also it seems to return all predictions with logits for each class (again assuming multi class instead of just 1 prob for the positive class). This is the code
and if i try to write a custom loss or metric, it returns inputs and targets of different shapes, one is of shape [bs, 2] the other [bs,1], they also seem to be logits and not probabilities so it’s hard to define the threshold. Can you please advice on what am I doing wrong?
It might be late, I leave my answer just in case someone has the same problem:
You are not doing anything wrong. If you want to use Sigmoid function and binary cross entropy for a binary classification problem, you can try (assuming you have one hidden layer)
