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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A small but persistent team of data scientists within Google’s Search Ads has been pursuing item #2 since about 2008, leading to a much improved understanding of the long-term user effects we miss when running typical short A/B tests. 2] Ron Kohavi, Randal M.

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Modeling Experimentation Knowledge Discovery Testing

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. Identical challenges are encountered in protein classification, where the number of proteins in one class is often much smaller than that of the proteins outside the class (Zhao et al., 30(2–3), 195–215. link] Ling, C. X., & Li, C.

Machine Learning

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Data Leaders Brief

Experiment design and modeling for long-term studies in ads

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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