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>Nobody has any scientifically cogent idea of what makes a model “explainable” other than arguing semantics. Bullshit, any client you show a regression to can

• ovi256 7y ago
  That's only true in some limited cases. Section 4.1 of the paper he linked discusses extensively the limitations of linear model interpretability. Here's an example: "With respect to algorithmic transparency, [the claim that linear models are more interpretable] seems uncontroversial, but given high dimensional or heavily engineered features, linear models lose simulatability or decomposability, respectively." Given how many interesting problems are high-dimensional or solved through heavy feature engineering, you must be lucky to live in the happy space where problems are either low-dimensional enough to not need heavy feature engineering or where the client is already familiar with the high-dimensional features you're going to limit the model to using.
• mlthoughts2018 7y ago
  I call bullshit on your comment, not mine. - http://www.saramitchell.org/achen04.pdf http://www.saramitchell.org/achen04.pdf The functional mechanism of a regression has nearly nothing to do with whether the regression explains the phenomenon it’s being used to model or not.