You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
LASSO implemented in glmnet and available in mlr3 (e.g. regr.glmnet) is a learner capable of extracting variable importance from the fitted model, but not yet in the mlr3learners package.
The text was updated successfully, but these errors were encountered:
There is no importance for glmnet learners, but you can extracted the features with non-zero coefficients with $selected_features(). For filtering, use FilterSelectedFeatures() (flt("selected_features")).
There are a lot of if-else blocks to cover all ways to call the learner which all yield slightly different objects. One way to extract the selected features is to predict the non-zero betas:
LASSO implemented in glmnet and available in mlr3 (e.g. regr.glmnet) is a learner capable of extracting variable importance from the fitted model, but not yet in the mlr3learners package.
The text was updated successfully, but these errors were encountered: