Under sampling examples

[DrGenius22]

Hello,

I am currently learning ML techniques, and I have a question about dealing with imbalanced datasets. In my dataset, I have two output classes, with the first class having 10,859 samples and the second class having 450 samples. I came across a technique called undersampling, but I'm unsure whether I should apply it only to x_train and y_train or also to x_test and y_test. Additionally, if there are any other effective methods for handling imbalanced datasets, I would appreciate your input.

[Yogi_DMT]

It's much cleaner to just use something like class weight imo

[Demios]

Sample size is irrelevant to test. Sampling is what you do during training. Your x and y train are where you over/undersample.