What is the relationship between Naïve Bayes and probabilistic hashing models?

Naïve Bayes can be combined with hashing tricks to approximate high-dimensional feature spaces efficiently.

Probabilistic hashing maps high-dimensional features into lower-dimensional fixed-size vectors. Naïve Bayes can then operate on hashed counts instead of full vocabulary representations. While this introduces collisions, it significantly reduces memory usage and enables scalable text classification in streaming environments.