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[ENH] Implement leakage-free imputation methods #2270

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fkiraly opened this issue Mar 21, 2022 · 2 comments

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enhancement good first issue implementing algorithms module:forecasting

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fkiraly commented Mar 21, 2022

The Imputer transformer has a lot of methods, but only few that are free of information leakage on a test set in the forecasting setting.

The simplest methods are implemented in #2269, but it would be nice to have more:

random_fit - like random, but uses min and max from fit
random_empirical - uses uniform sampling from the series seen in transform (this is leakage prone but should be there for completeness)
random_empirical_fit - uses uniform sampling from the series seen in fit
forecaster_fit - fits forecaster to data in fit, and uses predict to forecast indices with nan seen in transform

Implementation should branch off #2269 if not merged.

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fkiraly added good first issue implementing algorithms module:forecasting enhancement labels

divo12 commented Mar 22, 2022

I wish to contribute on it

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aiwalter commented Mar 22, 2022

I think we should rather implement this methods it fit as I described in the comments of #2269

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