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This repository has been archived by the owner on Jun 18, 2023. It is now read-only.
What do you think about renaming it to something along the lines of stay_regularized instead? I wrote the keyword argument keep_regularized and it even confuses me sometimes as to what that means (i.e., "keep" meaning retain the regularized coefficients or do we keep with the regularization that happened?).
Yes! I like stay_regularized much better since we want the coefficients that were regularized to stay regularized, as opposed to keeping the coefficients themselves.
refit_record function will retain keep_regularized kwarg for compatibility, but you can specify the behavior using stay_regularized in the config file. Just like the prefix, specify a list of True/False per refit method.
Need to expose
keep_regularized
argument for refit:keep_regularized = TRUE
If lasso regression coefficient is fit to
0
in change detection stage, don't fit in refit stage.keep_regularized = FALSE
Refit all coefficients in refit stage.
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