A dataset contains several records from each device. Random row splitting gives strong validation, but the model fails on new devices. Which correction best tests generalization to unseen devices?

1. Keep records from the same device together and split by device identity.
2. Duplicate every device in both splits to equalize the populations.
3. Increase model capacity before changing the validation design.
4. Remove device identifiers only after random splitting and assume all correlation disappears.