Advanced · Fundamentals

Bayesian Network

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A probabilistic graphical model representing a set of random variables and their conditional dependencies via a directed acyclic graph.

Technical Definition

A probabilistic graphical model representing a set of random variables and their conditional dependencies via a directed acyclic graph.

How it works

Bayesian networks model uncertain relationships between variables, where nodes represent variables and directed edges represent conditional dependencies. They leverage Bayes' theorem to update probabilities as new evidence becomes available, making them effective for reasoning under uncertainty. Applications range from medical diagnosis to natural language processing, providing a formal framework for probabilistic inference.