The DOI matches its Crossref record.
Learning on Bayesian Networks
Abstract
Learning procedures on Bayesian networks are studied on the basis of beta and Dirichlet distributions.
Overview
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Integrity signals
Registry
Cites
Statistics
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Claims the paper makes
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Self-check
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Citations
Cited by
Machine learning in bioinformatics
Larrañaga, P., Calvo, B., Santana, R., Bielza, C., Galdiano, J., Inza, I., Lozano, J. A., Armañanzas, R., Santafé, G., Pérez, A., et al. (2006) · Briefings in Bioinformatics · doi:10.1093/bib/bbk007 · Cited by 867
Metrics for evaluating performance and uncertainty of Bayesian network models
Marcot, B. G. (2012) · Ecological Modelling · doi:10.1016/j.ecolmodel.2012.01.013 · Cited by 380
Cai, B., Liu, Y., Fan, Q., Zhang, Y., Liu, Z., Yu, S., & Ji, R. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.09.043 · Cited by 329
Metadata
- Authors
- Vagis, A. A.
- Venue
- Journal of Automation and Information Sciences
- Publisher
- Begell House
- Published
- 2002
- Volume
- 34
- Issue
- 6
- Pages
- 5
- ISSN
- 1064-2315 (ISSN-L)
- OpenAlex
- W2034647518
- Cited by
- 404
- References
- 0
- FWCI
- 3.68
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Learning on Bayesian Networks. https://app.cochat.ai/papers/10.1615/jautomatinfscien.v34.i6.40
- The paper
- Vagis, A. A. (2002). Learning on Bayesian Networks. Journal of Automation and Information Sciences. https://doi.org/10.1615/jautomatinfscien.v34.i6.40
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
