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The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning
[article]
2022
arXiv
pre-print
Recent concerns that machine learning (ML) may be facing a reproducibility and replication crisis suggest that some published claims in ML research cannot be taken at face value. These concerns inspire analogies to the replication crisis affecting the social and medical sciences, as well as calls for greater integration of statistical approaches to causal inference and predictive modeling. A deeper understanding of what reproducibility concerns in research in supervised ML have in common with
arXiv:2203.06498v5
fatcat:shaduxgldfbphjwtedpoou2eme