right now I am working on a binary classification problem for images where I have to predict if there are tumor cells in an image or not.
By default the fastai library creates a custom head with two output channels because in the csv file no tumor is marked with 0 and tumor is marked with 1.
I am applying the thresholds on the prediction for “class” 1 (tumor) at the end and ignore the prediction for “class” 0 (no tumor).
But actually one output channel should be enough here and I am wondering if I should change the head to one output channel.
Does it make a performance difference if the model has one or two output channels for binary classification?
Thanks in advance,