We have a complete data set -> Check
Feature engineering done -> Check
How many variables do we have? 20 variables
How many should we ideally use ? Not more that 10 ideally
How to determine which variables to include and which not to ? Its simple do Boruta!!
Boruta is a feature selection algorithm. Precisely, it works as a wrapper algorithm around Random Forest. You can read about it here -> https://www.analyticsvidhya.com/blog/2016/03/select-important-variables-boruta-package/ Analytics vidhya has given a pretty good explanation about it here.
Now keep one important thing in mind we have two train sets 1)Normal train set 2)Smote Train set.
So upon running boruta on the normal train set, boruta confirmed the variables International_Plan,Voice_Mail_Plan ,No_Vmail_Messages,Total_Day_minutes,
Total_Night_Charge , Total_Intl_Minutes,Total_Intl_Calls,Total_Intl_Charge,
No_CS_Calls as important.
And upon running Boruta on Smote data set, Boruta confirmed all the variables as important, you can find the boruta code below