Hi!
I am wondering, which of the implemented sampling strategies handles unbalanced data best?
I believe if I get the top 10000 uncertain data instances, but 99 % are in the same class, this would not help much for the next training process iteration, right?
Thank you in advance!
Hi!
I am wondering, which of the implemented sampling strategies handles unbalanced data best?
I believe if I get the top 10000 uncertain data instances, but 99 % are in the same class, this would not help much for the next training process iteration, right?
Thank you in advance!