I trying to solve a linear regression problem and would like to select the most important variables to use. I came across the
Boruta package in R.
I am using it as follows:
important_feat <- Boruta(DepVar ~ IndepVar1 + IndepVar2 + IndepVar3, data=df)
DepVar is my continuous dependent variable that I want to estimate for the regression.
I would like to know if I am using Boruta correctly for feature selection in regression-based problems.