I'm running a LASSO regression on a continuous outcome, and am standardizing the features. Should I standardize the outcome as well?
Specifically I'm using the
glmnet R package.
From the glmnet doc:
Note also that for "gaussian" , glmnet standardizes y to have unit variance (using 1/n rather than 1/(n-1) formula) before computing its lambda sequence (and then unstandardizes the resulting co- efficients); if you wish to reproduce/compare results with other software, best to supply a stan- dardized y.
It depends on the distribution you are using/assuming as your response variable. If Gaussian or
mgaussian in glmnet nomenclature, then you can center scale.
The answer of whether it makes any difference really depends on the outcome type. If the outcome is binary, the standardization will make no difference. If Gaussian there are some differences between standardized and non-standardized outcomes which are already handled by an argument into the