Coverage vs. Accuracy: Striking a Balance in Data Science

The art of getting quick gains with agile model production

This post was written together with and inspired by Yuval Cohen

Introduction

Every day, numerous data science projects are discarded due to insufficient prediction accuracy. It’s a regrettable outcome, considering that often these models could be exceptionally well-suited for some subsets of the dataset.

Data Scientists often try to improve their models by using more complex models and by throwing more and more data at the …

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