I have a data set where I am doing a binary classification. I have close to 500 features and 200K observations. Now I also have few continuous variables as features.
I don't think just using these features just like that is right. Maybe some sort of transformation (log, sqrt etc.) is needed. How do I find out which transformation is the right transformation. Whether it need to be log, sqrt, squared or kernel function etc.
I do remember there is a technique called Power Transformation. It uses a formula to get the right transformation. Can someone guide here how to find the right transformation of the feature?