Dear Sklearn Team,
I want to fork the ProjectedGradientNMF -> DoubleProjectedGradientNMF code
with a minor change that I hope will have useful applications.
I want the code to work on two matrices M1, M2, which are aligned in the
observations (rows), but have different features. Then an observation of
features in the first may be used to find a reduced W, which may then yield
a prediction in the second set of features, and vice versa.
Compactly,
nmf_double(M1, M2) => W, H1, H2
I don't think this functionality is currently available. Useful suggestions
on how I go about forking this would be appreciated,
Best Wishes,
Alex
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