Feature Importance - a podcast by Ben Jaffe and Katie Malone

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.

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone