I understand GLMnet standardizes the predictor variables by default before fitting the model.
After fitting, the computed regression coefficients are then destandardized to allow reporting in their natural metric:
Is this the same for Caret using GLMnet? So if I get the coefficients for my final model for the best value of lambda by calling:
Are the coefficients related to standardized predictor variables or unstandarized predictor variables?
For example, say I am fitting an model using glmnet in caret for:
y = β0 + β1X1 + β2X2
and X1 is on a scale 0-1 but X2 is 1-100. To fit the model X1 and X2 would first be standardised to a mean of zero and a standard deviation of 1.
Would the reported coefficients β1 and β2 be for the standardised variables or for the unstandardized variables when using the Caret wrapper for GLMnet?