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Right now in the py version of the book, we tune the number of clusters manually (we run a pipeline for each $k$, manually extract results, plot). This was closer to the old version of the R book. New version of the R book uses tidyclust, which is more aligned with the classification/regression chapters in its tuning method.
Is there a similar update we can make to the py book?
Make sure to propagate this change to the worksheets if we do this.
The text was updated successfully, but these errors were encountered:
I had the same thought and looked at this briefly. Based on what I found, I don't think it is easily possible. See scikit-learn/scikit-learn#6154 for details. There are some workaround suggested on SO, but nothing convenient
Right now in the py version of the book, we tune the number of clusters manually (we run a pipeline for each$k$ , manually extract results, plot). This was closer to the old version of the R book. New version of the R book uses
tidyclust
, which is more aligned with the classification/regression chapters in its tuning method.Is there a similar update we can make to the py book?
Make sure to propagate this change to the worksheets if we do this.
The text was updated successfully, but these errors were encountered: