On the uniqueness of the expression for the choquet integral with linear core in classification

Weiwei Zhang, Wei Chen, Zhenyuan Wang

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

2 Scopus citations

Abstract

The Choquet integral has been applied in data mining, such as nonlinear multiregressions and nonlinear classifications. Adopting signed efficiency measures in the Choquet integral makes the models more powerful. Another idea for generalizing the above-mensioned models is to use a linear core in the Choquet integral. This has been successfully used in nonlinear mulregression. However, there is a uniqueness problem for presenting the Choquet integral in classification models such that it is difficult to explain the exact contribution rate from each individual attributes, as well as their combinations, towards the target. In this work, an additional restriction on the parameters is given to guarantee the uniqueness of the expression.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Granular Computing, GRC 2009
Pages769-774
Number of pages6
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Granular Computing, GRC 2009 - Nanchang, China
Duration: Aug 17 2009Aug 19 2009

Publication series

Name2009 IEEE International Conference on Granular Computing, GRC 2009

Other

Other2009 IEEE International Conference on Granular Computing, GRC 2009
Country/TerritoryChina
CityNanchang
Period8/17/098/19/09

Keywords

  • Classification
  • Data mining
  • Fuzzy measures
  • Nonlinear integrals

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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