FuzzyCART: a novel fuzzy logic based classification & regression trees algorithm

  • Authors:
  • P. R. J. Campbell;H. Fathulla;F. Ahmed

  • Affiliations:
  • College of Information Technology, United Arab Emirates University, UAE;Department of Computing & Mathematics, Manchester Metropolitan University, UK;College of Information Technology, United Arab Emirates University, UAE

  • Venue:
  • IIT'09 Proceedings of the 6th international conference on Innovations in information technology
  • Year:
  • 2009

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Abstract

Classification algorithms have found high levels of application in a range of domains. One of the most important classification algorithms that is currently in wide use Classification And Regression Trees (CART), which yields accurate and consistent results in most multiple domains. A significant failing of CART and other similar algorithms is their inability to handle imprecision. This inability to handle the "grey areas" makes these algorithms less applicable to a range of domains such as Medicine and Finance. A wellregarded method for handling such imprecision is Fuzzy Logic, and in this paper a novel algorithm that combines CART and Fuzzy Logic is presented. Following the description of the implementation the experimental results presented which have been achieved through the use of the proposed FuzzyCART algorithm demonstrate an increased level of classification accuracy for medical data when compared to classical CART.