Nonlinear nonnegative multiregressions based on Choquet integrals

Zhenyuan WANG, Kwong-Sak LEUNG, Man-Leung WONG, Jian FANG, Kebin XU

Research output: Journal PublicationsJournal Article (refereed)

42 Citations (Scopus)

Abstract

Using a nonadditive set function to describe the interaction among attributes, a new nonlinear nonnegative multiregression is established based on Choquet integrals with respect to the set function. Regarding the values of the set function as unknown regression parameters, an evolutionary computation can be used to determine them when necessary data are available. Such a model is a generalization of the traditional linear multiregression. It provides an e€ective regression tool in some real problems where the linear multiregression model and the second-order multiregression model fail. This new method has a wide applicability in the areas of information fusion and data mining, as well as in the areas of decision making, image processing, pattern recognition, medical and industrial diagnoses, and expert systems.
Original languageEnglish
Pages (from-to)71-87
Number of pages17
JournalInternational Journal of Approximate Reasoning
Volume25
Issue number2
DOIs
Publication statusPublished - Oct 2000
Externally publishedYes

Keywords

  • Nonlinear regressions
  • Information fusion
  • Data mining
  • Nonnegative monotone set functions
  • Choquet integrals
  • Optimization
  • Evolutionary algorithms

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