Artificial immune system for attribute weighted Naive Bayes classification

Jia Wu, Zhihua Cai, Sanyou Zeng, Xingquan Zhu

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

26 Citations (Scopus)

Abstract

Naive Bayes (NB) is a popularly used classification method. One potential weakness of NB is the strong conditional independence assumption between attributes, which may deteriorate the classification accuracy. In this paper, we propose a new Artificial Immune System based Weighted Naive Bayes (AISWNB) classifier. AISWNB uses immunity theory in artificial immune systems to find optimal weight values for each attribute. The adjusted weight values will alleviate the conditional independence assumption and help calculate the conditional probability in an accurate way. Because AISWNB uses artificial immune system search mechanism to find optimal weights, it does not need to know the importance of individual attributes nor the relevance among attributes. As a result, it can obtain optimal weight value for each attribute during the learning process. Experiments and comparisons on 36 benchmark data sets demonstrate that AISWNB outperforms other state-of-the-art attribute weighted NB algorithms.
Original languageEnglish
Title of host publicationThe 2013 International Joint Conference on Neural Networks (IJCNN)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-8
Number of pages8
ISBN (Electronic)9781467361286
DOIs
Publication statusPublished - 1 Aug 2013
Externally publishedYes
Event2013 International Joint Conference on Neural Networks, IJCNN 2013 - Dallas, United States
Duration: 4 Aug 20139 Aug 2013

Conference

Conference2013 International Joint Conference on Neural Networks, IJCNN 2013
CountryUnited States
CityDallas
Period4/08/139/08/13

Keywords

  • artificial immune systems
  • Bayes methods
  • pattern classification
  • probability
  • attribute weighted Naive Bayes classification
  • artificial immune system based weighted Naive Bayes classifier
  • AISWNB
  • immunity theory
  • optimal weight values
  • conditional independence assumption
  • conditional probability
  • artificial immune system search mechanism
  • learning process
  • Niobium
  • Immune system
  • Accuracy
  • Cloning
  • Sociology
  • Statistics
  • Mutual information

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