Ordinal decision trees based on fuzzy rank entropy

Xin WANG, Junhai ZHAI*, Jiankai CHEN, Xizhao WANG

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

4 Citations (Scopus)

Abstract

Ordinal classification problems widely exist in the real world, and ordinal decision tree is one of the most important ways of dealing with the ordinal classification problems. In this paper, we introduce the fuzzy rank entropy and design a new ordinal decision tree algorithm (FREMT) based on the fuzzy rank mutual information, which is an extension of ordinal decision tree. The proposed algorithm selects the fuzzy rank mutual information as a split criterion, and it can not only be applied in crisp ordinal set, but also be used in the fuzzy ordinal set The numerical experiments show that its performance is superior to other methods as well as rank mutual information based ordinal decision tree algorithm (REMT).
Original languageEnglish
Title of host publicationProceedings of 2015 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2015
PublisherIEEE
Pages208-213
Number of pages6
ISBN (Electronic)9781467372244
DOIs
Publication statusPublished - 9 Oct 2015
Externally publishedYes
Event2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR) - Holiday Inn Guangzhou Shifu, Guangzhou, China
Duration: 12 Jul 201515 Jul 2015

Conference

Conference2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)
Country/TerritoryChina
CityGuangzhou
Period12/07/1515/07/15

Keywords

  • Fuzzy rank mutual information
  • Ordinal classification
  • Ordinal decision tree

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