Naïve Bayes variants in classification learning

Khadija Mohammad Al-Aidaroos, Azuraliza Abu Bakar, Zalinda Othman

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

12 Citations (Scopus)

Abstract

Naïve Bayesian classifier is one of the most effective and efficient classification algorithms. The elegant simplicity and apparent accuracy of naive Bayes (NB) even when the independence assumption is violated, fosters the on-going interest in the model. This paper discusses issues on NB along with its advantages and disadvantages. We also present an overview of NB variants and provide a categorization of those methods based on four dimensions. These include manipulating the set of attributes, allowing interdependencies, employing local learning and adjusting the probabilities by numeric weights. Examples for each category are discussed based on 18 variants reviewed in this paper.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10
Pages276-281
Number of pages6
DOIs
Publication statusPublished - 2010
EventInternational Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10 - Shah Alam
Duration: 17 Mar 201018 Mar 2010

Other

OtherInternational Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10
CityShah Alam
Period17/3/1018/3/10

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Classifiers

Keywords

  • Classification learning
  • Naïve Bayes (NB) classifier
  • NB variants

ASJC Scopus subject areas

  • Information Systems

Cite this

Al-Aidaroos, K. M., Abu Bakar, A., & Othman, Z. (2010). Naïve Bayes variants in classification learning. In Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10 (pp. 276-281). [5466902] https://doi.org/10.1109/INFRKM.2010.5466902

Naïve Bayes variants in classification learning. / Al-Aidaroos, Khadija Mohammad; Abu Bakar, Azuraliza; Othman, Zalinda.

Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10. 2010. p. 276-281 5466902.

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

Al-Aidaroos, KM, Abu Bakar, A & Othman, Z 2010, Naïve Bayes variants in classification learning. in Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10., 5466902, pp. 276-281, International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10, Shah Alam, 17/3/10. https://doi.org/10.1109/INFRKM.2010.5466902
Al-Aidaroos KM, Abu Bakar A, Othman Z. Naïve Bayes variants in classification learning. In Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10. 2010. p. 276-281. 5466902 https://doi.org/10.1109/INFRKM.2010.5466902
Al-Aidaroos, Khadija Mohammad ; Abu Bakar, Azuraliza ; Othman, Zalinda. / Naïve Bayes variants in classification learning. Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10. 2010. pp. 276-281
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