I have a large dataset with many variables (for example: height, weight, color, category, revenue...)
I am trying to compare two groups and find which variables determine the groups. My goal would be to narrow down the variables and be able to pick a small number of variables that would be able to determine which group a record belongs to.
For instance compare group A (top 1% revenue) to group B (bottom 99% revenue) and determine which variables are causing the items to be in the different revenue groups.
What method would I use to accomplish this?
I think a method like SVM would be used to classify which group (A or B) an entry would fit into.
What I'm trying to do is find which of the variables (ie: height, weight, color...) have a determining effect on the classification. I'd like to be able to choose a small number of the variables that make a difference.
Is there a method to accomplish this?