EPISODE · Mar 27, 2017 · 20 MIN
Feature Importance
from Linear Digressions · host 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.
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