2008, Knowledge Discovery, Metrics and Testing

Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.

Modeling

Modeling Experimentation Knowledge Discovery Testing

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic. Chawla et al.,

Machine Learning

Machine Learning Metrics Data mining Knowledge Discovery

Data Leaders Brief

Experiment design and modeling for long-term studies in ads

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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