I am using gbm(R's caret packages - using train function) on a class imbalanced data set with weights. So, class-1 has a weight of 1 and class-0 has a weight of 10. I am using parameter tuning and minimising AUC. I want to ask that is you are using weights in gbm with a class imbalanced data set then you are atificially making the classifier to put more focus towards the minority class and AUC/ROC is used mainly to check the sensitity & specificity trade-off. Does it make sense to minimise AUC with weights in GBM? or it should be accuracy? Please ignore my lack of understanding.
Thanks.