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Data science tutorial: causal inference model selection | Jonathan Hershaff
Like hyper-parameter tuning, model selection techniques are commonplace in machine learning but often overlooked in the causal inference space. I've sat in plenty of seminars with data scientists who had a time series and a limited set of treated units who chose a model and went with it without testing alternatives. This can have important ...
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