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Handle NaNs #213

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Handle NaNs #213

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sjsrey
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@sjsrey sjsrey commented May 29, 2024

This will add functionality to handle missing values encoded as numpy.NaN.

The proposal is to classify the masked values (excluding NaNs), and then set the bin label for the missing observations to -1.

This would keep the labels as ints, rather than using numpy.NaN which would change the labels to floats.

This is a work-in progress PR to solicit comments and ideas.

@sjsrey sjsrey added WIP Work in progress. For discussion and feedback. Do not merge. enhancement labels May 29, 2024
@knaaptime
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sweet. looks like the only failure is probably small?

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@sjsrey do you want to get this into meta, or hang on until the next?

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sjsrey commented Jul 3, 2024

@sjsrey do you want to get this into meta, or hang on until the next?

Hang on.

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