Data classification using rough sets and naïve bayes

Khadija Al-Aidaroos, Azuraliza Abu Bakar, Zalinda Othman

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

5 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. Rough Sets Theory has been used for different tasks in knowledge discovery and successfully applied in many real-life problems. In this study we make use of rough sets ability, in discovering attributes dependencies, to overcome the NB un-practical assumption. We propose a new algorithm called Rough-Naive Bayes (RNB) that is expected to outperform other current NB variants. RNB is based on adjusting attributes' weights based on their dependencies and contribution to the final decision. Experimental results show that RNB can achieve better performance than NB classifier.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages134-142
Number of pages9
Volume6401 LNAI
DOIs
Publication statusPublished - 2010
Event5th International Conference on Rough Set and Knowledge Technology, RSKT 2010 - Beijing
Duration: 15 Oct 201017 Oct 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6401 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Conference on Rough Set and Knowledge Technology, RSKT 2010
CityBeijing
Period15/10/1017/10/10

Fingerprint

Data Classification
Naive Bayes
Bayes
Rough Set
Classifiers
Rough set theory
Rough
Data mining
Attribute
Naive Bayes Classifier
Bayesian Classifier
Rough Set Theory
Knowledge Discovery
Classification Algorithm
Simplicity
Efficient Algorithms
Experimental Results

Keywords

  • attribute dependency
  • Classification
  • Naïve Bayes (NB)
  • NB variants
  • Rough Sets (RS)
  • weighted NB

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Al-Aidaroos, K., Abu Bakar, A., & Othman, Z. (2010). Data classification using rough sets and naïve bayes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6401 LNAI, pp. 134-142). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI). https://doi.org/10.1007/978-3-642-16248-0_23

Data classification using rough sets and naïve bayes. / Al-Aidaroos, Khadija; Abu Bakar, Azuraliza; Othman, Zalinda.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. p. 134-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI).

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

Al-Aidaroos, K, Abu Bakar, A & Othman, Z 2010, Data classification using rough sets and naïve bayes. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6401 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6401 LNAI, pp. 134-142, 5th International Conference on Rough Set and Knowledge Technology, RSKT 2010, Beijing, 15/10/10. https://doi.org/10.1007/978-3-642-16248-0_23
Al-Aidaroos K, Abu Bakar A, Othman Z. Data classification using rough sets and naïve bayes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI. 2010. p. 134-142. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-16248-0_23
Al-Aidaroos, Khadija ; Abu Bakar, Azuraliza ; Othman, Zalinda. / Data classification using rough sets and naïve bayes. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. pp. 134-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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