Which mathematical model is NOT commonly used in retail personalization algorithms for customer behavior prediction?

Personalization algorithms power modern retail experiences, delivering tailored product recommendations and offers to customers. These sophisticated systems rely heavily on mathematical concepts and models to transform customer data into actionable insights. This poll tests your knowledge of the mathematical foundations that drive these powerful retail personalization engines that have revolutionized how retailers connect with customers.

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Markov Decision Processes
Non-negative Matrix Factorization
Ordinary Differential Equations
Bayesian Networks