OTCP tutorial #613
OTCP tutorial #613
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base draft tutorial otcp
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- please remove the unused
RandomForestRegressor - for imports (either ours or external packages), let's not import the classes directly (e.g.,
from ott.tools.conformal import OTCP), but let's use, e.g.from ott.tools import conformaland laterotcp = conformal.OTCP(...). Same applies for thesklearnpackages.
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I think it's important we add link to the original dataset where it comes from. Furthermore, since we're downloading from the 2nd publication you mention, I'd mention only that one + add it as a citation in the bibliography and use {cite}. dheur:25
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No need to have display(df.head()), you can just to df on the last line when executing the notebook cell.
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Line #34. x=confidence_regions[idx, :, 1].flatten(),
Don't think .flatten() is needed.
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Line #42. label="Contour of Confidence Region",
This can also be removed, it's not being shown.
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Line #3. y_candidates = jnp.array(Y_train[:500])
Maybe it would be more interesting here to provide a 2D grid instead of sampling the candidates from y_train.
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base draft tutorial otcp