My goal is to make binary classification, using neural network. The problem is that dataset is unbalanced, I have 90% of class 1 and 10 of class 0. To deal with it I want to use Stratified cross-validation.
The problem that is I am working with Pytorch, I can't find any example and documentation doesn't provide it, and I'm student, quite new for neural networks.
Can anybody help? Thank you!
The easiest way I've found is to do you stratified splits before passing your data to Pytorch Dataset and DataLoader. That lets you avoid having to port all your code to skorch, which can break compatibility with some cluster computing frameworks.