A Probability Requirement Functor Model (PRF model) is a distinct model type - not a variant of a neural network and not positioned against one. It represents a prediction system as a set of named, typed probability functions, served through an aggregator and kept current by explicit, auditable updates. The spirit of the PRF is traceability. The requirements of the user and various distributions they include in the model are cleanly separated and visible. For business and scientific purposes there is no question as to what the model is doing.
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John Harby (2026) studied this question.
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