bnclassify: Learning Bayesian Network Classifiers

Mihaljevic, Bojan and Bielza Lozoya, María Concepción and Larrañaga Múgica, Pedro María (2018). bnclassify: Learning Bayesian Network Classifiers. "R JOURNAL", v. 10 (n. 2); pp. 455-468. ISSN 2073-4859.


Title: bnclassify: Learning Bayesian Network Classifiers
  • Mihaljevic, Bojan
  • Bielza Lozoya, María Concepción
  • Larrañaga Múgica, Pedro María
Item Type: Article
Título de Revista/Publicación: R JOURNAL
Date: 2018
ISSN: 2073-4859
Volume: 10
Freetext Keywords: bnclassify package
Faculty: E.T.S.I. de Sistemas Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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The bnclassify package provides state-of-the art algorithms for learning Bayesian network classifiers from data. For structure learning it provides variants of the greedy hill-climbing search, a well-known adaptation of the Chow-Liu algorithm and averaged one-dependence estimators. It provides Bayesian and maximum likelihood parameter estimation, as well as three naive-Bayes-specific methods based on discriminative score optimization and Bayesian model averaging. The implementation is efficient enough to allow for time-consuming discriminative scores on medium-sized data sets. bnclassify provides utilities for model evaluation, such as cross-validated accuracy and penalized log-likelihood scores, and analysis of the underlying networks, including network plotting via the Rgraphviz package. It is extensively tested, with over 200 automated tests that give a code coverage of 94%. Here we present the main functionalities, illustrate them with a number of data sets, and comment on related software.

Funding Projects

Horizon 2020785907HBP SGA2Universidad Politécnica de MadridHuman Brain Project Specific Grant Agreement 2
Government of SpainC080020-09UnspecifiedUnspecifiedCajal Blue Brain Project
Government of SpainTIN2016-79684-PUnspecifiedUnspecifiedAvances en clasificación multidimensional y detección de anomalías con redes bayesianas
Madrid Regional GovernmentS2013/ICE-2845-CASI-CAM-CMUnspecifiedFrancisco Javier MonteroConceptos y aplicaciones de los sistemas inteligentes

More information

Item ID: 54545
DC Identifier:
OAI Identifier:
DOI: 10.32614/rj-2018-073
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 22 Jan 2020 13:20
Last Modified: 22 Jan 2020 13:20
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