Construct · 1 fields · 1 citations

selective labels problem: a standalone construct

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selectivelabels problem1 CONSTRUCTSelective labels problemLAKKARAJU · MACHINE LEARNING

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Machine learning

evaluating algorithmic decisions when outcomes are observed only for cases that past human decisions allowed, such as defendants who were released.

In machine learning, selective labels problem refers to evaluating algorithmic decisions when outcomes are observed only for cases that past human decisions allowed, such as defendants who were released. This meaning comes from Lakkaraju (2017) in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.[1]

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Nearby constructs

knowledge6 fields · 12 citationsjingle · one name, six constructslearning6 fields · 14 citationsjingle · one name, six constructsmine2 fields · 2 citationsjingle · one word, two constructs

References

  1. Lakkaraju, H., Kleinberg, J., Leskovec, J., Ludwig, J., & Mullainathan, S. (2017). The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. https://doi.org/10.1145/3097983.3098066

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