My question is rather simple what does the parameter scale_pos_weight in xgboost do? I know typically it should be $\frac{sum(negative cases)}{sum(positive cases)}$.Does it oversample the minority class by that ratio or does it undersample the majority class by inverse of that ratio? Or something else?Also I would like to know if during cross validation in xgbcv, does the sampling happen on the test part of the cross-validation also or only the train part is affected by scale_pos_weight? Because i've heard that sampling should never be applied to test as it gives over-optimistic results. 
scale_pos_weight Xgboost
classification;xgboost;unbalanced classes