I am working on a regression problem where I have a lot of outliers in multiple variables. As far as I can think of, there are 3 things I can do to outliers.
Remove them (least attractive option)
Transform them (log transformation, box-cox transformation etc)
Do nothing and build a model including them
My question is regarding the second point. If I want to transform my features using any of the transformations solely for the purpose of outlier, is it ok to do it?