2015, Knowledge Discovery, Measurement and Metrics

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. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

Modeling

Modeling Experimentation Knowledge Discovery Testing

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. 2015) for additional details. See Wei et al. Bahdanau, D.,

Modeling

Modeling Deep Learning Machine Learning Knowledge Discovery

Data Leaders Brief

Experiment design and modeling for long-term studies in ads

Explaining black-box models using attribute importance, PDPs, and LIME

Webinars

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