Implementing Adaptive Vectorial Centroid in Bayesian Logistic Regression for Interval Type-2 Fuzzy Sets

  title={Implementing Adaptive Vectorial Centroid in Bayesian Logistic Regression for Interval Type-2 Fuzzy Sets},
  author={Ku Muhammad Naim Ku Khalif and Alexander E. Gegov},
A prior distributions in standard Bayesian knowledge are assumed to be classical probability distribution. It is required to representable those probabilities of fuzzy events based on Bayesian knowledge. Propelled by such real applications, in this research study, the theoretical foundations of Vectorial Centroid of interval type-2 fuzzy set with Bayesian logistic regression is introduced. As opposed of utilising type-1 fuzzy set, type-2 fuzzy set is recommended based on the involvement of… 
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  • N. MogharrebanL. DiLalla
  • Computer Science
    NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society
  • 2006
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