Artificial Intelligence Programming Practice Exam 2025 - Free AI Programming Practice Questions and Study Guide

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What type of graph does a Bayesian network use?

Circular graph

Directed acyclic graph

A Bayesian network uses a directed acyclic graph (DAG) structure to represent a set of variables and their conditional dependencies through directed edges. In this context, each node represents a random variable, and the directed edges indicate the direction of influence or causal relationships among those variables. The acyclic nature of the graph means that there are no cycles or loops, ensuring that if you follow the directed edges, you cannot return to a node you’ve already visited.

This structure is essential for performing probabilistic inference because it allows the network to effectively capture the dependencies between the variables without the complications that cycles would introduce. By maintaining a directed and acyclic structure, Bayesian networks can efficiently represent and reason about uncertainty in complex systems, making them powerful tools in various fields like statistics, machine learning, and artificial intelligence.

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Weighted tree

Undirected graph

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