Python Select variables in multiple linear regression
You are probably looking for a k-fold validation model.
The idea is to randomly select your features, and have a way to validate them against each other.
The idea is to train your model with your feature selection on (k-1) partitions of your data. And validate it against the last partition. You do it for each partition and take the average of your score (MAE / RMSE for instance)
Your score is an objectif figure to compare your models aka your features selections
I have a dependent variable y and 6 independent variables. I want to make a linear regression out of it. I use sklearn library to do it. 
The problem is some of my independent variables have correlation more than 0.5. So I can't have them in my model at the same time 
I searched throw internet but didn't find any solution to select best set of independent variables to draw linear regression and output the variables that had been selected.