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Quantitative probing: Validating causal models with quantitative domain knowledge

We propose quantitative probing as a model-agnostic framework for validating causal models in the presence of quantitative domain knowledge. The method is constructed in analogy to the train/test split in correlation-based machine learning. It is consistent with the logic of scientific discovery and...

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Váldodahkkit: Grünbaum Daniel, Stern Maike L., Lang Elmar W.
Materiálatiipa: Artigo
Giella:Inglês
Almmustuhtton: De Gruyter 2023-07-01
Ráidu:Journal of Causal Inference
Fáttát:
Liŋkkat:https://doi.org/10.1515/jci-2022-0060
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