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Inclusion of additional constraints (typically a penalty for complexity) in the model fitting process. Used to prevent overfitting / enhance predictive accuracy.
21
votes
Advantages of doing "double lasso" or performing lasso twice?
The idea is to separate the two effects of lasso
Variable selection (i.e., many, even most, $\beta$s are zero)
Coefficient shrinkage (i.e., even non-zero $\beta$s are smaller, in absolute value, tha …