Hi,
Is there any way to do GridSearch on multiple scoring functions without
having to repeat the fit/predict process for each function?
(e.g.: grid_search_digits.py - In this example, GridSearch is run twice,
once each for precision and recall. )
Possible Solution: Manual approach. Use IterGrid and take care of
fit/predict/scoring manually.
Problem: But this means I have to forego the library's builtin
parallelization features which *really* speed things up. (n_jobs=-1 :) )
Thanks,
Karthick
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