Feature Importance

Linear Digressions - En podcast af Ben Jaffe and Katie Malone

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Figuring out what features actually matter in a model is harder to figure out than you might first guess.  When a human makes a decision, you can just ask them--why did you do that?  But with machine learning models, not so much.  That's why we wanted to talk a bit about both regularization (again) and also other ways that you can figure out which models have the biggest impact on the predictions of your model.

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