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Thresholdout: Down with Overfitting
Linear Digressions
English - November 27, 2015 17:55 - 15 minutes - 21.8 MB - ★★★★★ - 350 ratingsTechnology data science machine learning linear digressions Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: The State of Data Science
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