I have data that I will use as a feature to Elastic Net. I thought I should transform the data using either Box Cox or Yeo Johnson.
The transformed data looks weird and I'm not sure if I should transform the data or not.
Besides the large bar at -2 for Yeo Johnson the distribution looks ok, but I'm not sure if large amount of values around -2 will affect model performance or not.
So my question is, is it always safe to transform the data? I.e. can it affect model performance, in a negative way, by transforming the data?