PLAY PODCASTS
Thresholdout: Down with Overfitting

Thresholdout: Down with Overfitting

Overfitting to your training data can be avoided …

Linear Digressions

November 27, 201515m 52s

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

Overfitting to your training data can be avoided by evaluating your machine learning algorithm on a holdout test dataset, but what about overfitting to the test data? Turns out it can be done, easily, and you have to be very careful to avoid it. But an algorithm from the field of privacy research shows promise for keeping your test data safe from accidental overfitting

Topics

datasciencemachinelearninglineardigressions