feedzai / fairgbm

Train Gradient Boosting models that are both high-performance *and* Fair!

Home Page:https://arxiv.org/abs/2209.07850

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Handle missing values for sensitive attributes

AndreFCruz opened this issue · comments

Summary

LightGBM allegedly handles missing values in the features (e.g., represented as NaN).
We should also be able to handle missing values in the constraint group column (sensitive attribute).

For instance, we could do imputation with the majority group for all rows with unknown sensitive attribute.