Naturally, my first idea was to transform the target with natural logarithm as it'll probably help both linear regression or decision-tree-based algorithms. The second idea is to prepare a validation scheme similar to stratified k-fold cross-validation with target binned into n groups. However, my concern is that I have only few highest values:
Therefore, my test set and all validation sets error are highly dependent if one of these 4 extreme values are drawed placed within them or not. That makes it hard to obtain reliable true error estimate.
Is there anything more I can do to handle that issue?