A Bayesian Method for Constructing Bayesian Belief Networks from Databases
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Abstract (arXiv)
This paper presents a Bayesian method for constructing Bayesian belief networks from a database of cases. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabilistic expert systems. Results are presented of a preliminary evaluation of an algorithm for constructing a belief network from a database of cases. We relate the methods in this paper to previous work, and we discuss open problems.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Mar 2013.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 1.
4 papers.
- 2021Partitioned hybrid learning of Bayesian network structurescited by 4
- 2024Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networkscited by 2
- 2021Needmining: Designing Digital Support to Elicit Needs from Social Mediacited by 1
- 2021How do some Bayesian Network machine learned graphs compare to causal knowledge?cited by 1
- 2024Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks25 Jun 2024
- 2021Partitioned hybrid learning of Bayesian network structures22 Mar 2021
- 2021How do some Bayesian Network machine learned graphs compare to causal knowledge?25 Jan 2021
- 2021Needmining: Designing Digital Support to Elicit Needs from Social Media14 Jan 2021