2010, Predictive Modeling and Statistics

Proposals for model vulnerability and security

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling

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Using random effects models in prediction problems

The Unofficial Google Data Science Blog

MARCH 31, 2016

Finally, through a case study of a real-world prediction problem, we also argue that Random Effect models should be considered alongside penalized GLM's even for pure prediction problems. Random effects models are a useful tool for both exploratory analyses and prediction problems. 5] Anoop Korattikara, et al.

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Data Leaders Brief

Proposals for model vulnerability and security

Using random effects models in prediction problems

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