Construct · 1 fields · 1 citations
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In causal inference, meta-learners refers to strategies for estimating heterogeneous treatment effects by combining any machine learning regressors in set ways, such as separate or cross-fitted outcome models. This meaning comes from Künzel (2019) in Proceedings of the National Academy of Sciences.[1]
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