PLAY PODCASTS
Maximal Margin Classifiers

Maximal Margin Classifiers

Maximal margin classifiers are a way of thinking …

Linear Digressions

December 4, 201714m 21s

Audio is streamed directly from the publisher (feeds.soundcloud.com) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.

Show Notes

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!

Topics

datasciencemachinelearninglineardigressions