Bayesian Belief Network in AI Quiz
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Questions and Answers

What is a Bayesian network?

  • A probabilistic graphical model representing variables and their conditional dependencies using a directed acyclic graph (correct)
  • A model representing variables and their unconditional dependencies using an undirected cyclic graph
  • A deterministic mathematical model for solving decision problems
  • A machine learning algorithm for unsupervised clustering
  • What is another name for a Bayesian network?

  • Belief network (correct)
  • Support vector machine
  • Markov network
  • Decision tree
  • Why are Bayesian networks considered probabilistic?

  • Because they always yield uncertain outcomes
  • Because they are based on fuzzy logic
  • Because they are built from a probability distribution and use probability theory for prediction and anomaly detection (correct)
  • Because they rely on deterministic algorithms
  • What type of graph is used to represent a Bayesian network?

    <p>Directed acyclic graph (DAG)</p> Signup and view all the answers

    What is the generalized form of a Bayesian network for solving decision problems under uncertain knowledge?

    <p>Influence diagram</p> Signup and view all the answers

    Study Notes

    Bayesian Networks

    • A Bayesian network is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG).

    Alternative Name

    • A Bayesian network is also known as a Bayes net or belief network.

    Probabilistic Nature

    • Bayesian networks are considered probabilistic because they model uncertainty using probability theory, allowing for the quantification of uncertainty and the updating of beliefs based on new evidence.

    Graph Representation

    • A Bayesian network is represented using a directed acyclic graph (DAG), which consists of nodes representing variables and edges representing conditional dependencies between variables.

    Generalized Form for Decision-Making

    • The generalized form of a Bayesian network for solving decision problems under uncertain knowledge is called an influence diagram, which extends the Bayesian network to include decision and utility nodes to model decision-making under uncertainty.

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    Test your knowledge about Bayesian belief networks, a key technology in artificial intelligence for handling probabilistic events and uncertainty. Learn about probabilistic graphical models, variable dependencies, and directed acyclic graphs.

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