Hello,
This is Farzana. I am trying to understand the attribute incremental
learning ( or virtual concept drift) which is every time when a new
feature will be available for a real-time dataset (i.e. any online
auction dataset) a classifier will add that new feature with the
existing features in a dataset and classify the new dataset (with
previous features and new features) incrementally. I know that we can
convert a static classifier to an incremental classifier in
scikit-learn. However, I could not find any library or function for
attribute incremental learning or any detail information. It would be
great if anyone could give me some insight on this.
Thanks!
--
Best Regards,
Farzana Anowar,
PhD Candidate
Department of Computer Science
University of Regina
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