_carltg

6 ms·

1. 1.▲
   by _carltg 1y ago

   The problem is the methodology they use to hold them out. For a truly independent validation set, they need to hold out the material before augmentation, not after. If you hold out after augmentation, then you leverage biases from the train
2. 2.▲
   by _carltg 1y ago

   Yes, but due to it being derived from the same underlying source dataset, it is effectively evaluating on the training dataset, not an independent validation/ test dataset. The difference is subtle but important. If we expect the model
3. 3.▲
   by _carltg 1y ago

   Yes, this is the main concern I have with this result as well. In other words, rather than plucking different leaves (augments) from the same branch or tree (source dataset), you should be evaluating it on an entirely different tree. This p