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On Prediction Feature Assignment in the Heckman Selection Model
This paper focuses on one classic instance of MNAR sample selection bias where a subset of samples have non-randomly missing outcomes.
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
In this paper, we propose BiasCorr, an algorithm that improves on Greene's method by modifying the original training set in order for a classifier to learn under MNAR sample selection bias.
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