scikit-learn: machine learning in Python. Please feel free to ask specific questions about scikit-learn. Please try to keep the discussion focused on scikit-learn usage and immediately related open source projects from the Python ecosystem.
sample_weigth
or class_weigth
will allow you to play on the inner loss
maybe it could go on scikit-learn discussions as well :)
+1. As mentioned in https://github.com/scikit-learn/scikit-learn/discussions/19220#discussioncomment-298015 my feeling (and probably others feeling) is that gitter is not the best place for Q&A. I guess a reasonable approach is to create a discussion and then ping on gitter if you feel you have not received an answer after some time
Hi All. Had a question about a possible discrepancy between user guide and autogenerated docs for LASSO Linear model. Auto-gen docs (https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html) says that:
(1 / (2 * n_samples)) * ||y - Xw||^2_2 + alpha * ||w||_1
Is minimised. However, the user guide seems to to imply that it's ||Xw - y||
rather than ||y-Xw||
(https://scikit-learn.org/stable/modules/linear_model.html#lasso). y-Xw
makes more sense to me. Am I reading something incorrectly, or is the user guide wrong?