Or gate Bayesian networks for text classification: A discriminative alternative approach to multinomial naive Bayes

Luis M. de Campos, J.M. Fernández-Luna, J.F. Huete, Alfonso E. Romero

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We propose a simple Bayesian network-based text classifier, which may be considered as a discriminative counterpart of the generative multinomial naive Bayes classifier. The method relies on the use of a fixed network topology with the arcs going form term nodes to class nodes, and also on a network parametrization based on noisy or gates. Comparative experiments of the proposed method with naive Bayes and Rocchio algorithms are carried out using three standard document collections.
Original languageEnglish
Title of host publicationActas del XIV Congreso Español sobre Tecnologías y Lógica Fuzzy
Number of pages6
Publication statusPublished - 2008
EventXIV Congreso Español sobre Tecnologías y Lógica Fuzzy, ESTYLF 2008 - Mieres-Langreo, Spain
Duration: 17 Sept 200819 Sept 2008


ConferenceXIV Congreso Español sobre Tecnologías y Lógica Fuzzy, ESTYLF 2008


  • Bayesian network
  • noisy or gate
  • multinomial naive Bayes
  • text classification

Cite this