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Podcast: Linear Digressions
Episode:

Maximal Margin Classifiers
Category: Technology
Duration: 00:14:21
Publish Date: 2017-12-03 22:03:02
Description: Maximal margin classifiers are a way of thinking about supervised learning entirely in terms of the decision boundary between two classes, and defining that boundary in a way that maximizes the distance from any given point to the boundary. It's a neat way to think about statistical learning and a prerequisite for understanding support vector machines, which we'll cover next week--stay tuned!
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