2008, Knowledge Discovery, Metrics and Modeling

Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling

Modeling Experimentation Knowledge Discovery Testing

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. def get_neigbours(M, k): nn = NearestNeighbors(n_neighbors=k+1, metric="euclidean").fit(M) Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79.

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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