A new algorithm for solving convex hull problem and its application to feature selection

Feng GUO, Xi-Zhao WANG, Yan LI

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

4 Citations (Scopus)

Abstract

A new method to solve the convex hull problem in n-dimensional spaces is proposed in this paper. At each step, a new point is added into the convex hull if the point is judged to be out of the current convex hull by a linear programming model. For the linear separable classification problem, if an instance is regarded as a point of the instances space, the overlap does not still occur between the convex hulls of different classes after a feature is deleted, then we can delete that feature. Repeat this process, an algorithm for feature selection is given. Experimental results show the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
PublisherIEEE
Pages369-373
Number of pages5
ISBN (Print)9781424420957
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China
Duration: 12 Jul 200815 Jul 2008

Publication series

NameInternational Conference on Machine Learning and Cybernetics (ICMLC)
PublisherIEEE
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference7th International Conference on Machine Learning and Cybernetics, ICMLC
Country/TerritoryChina
CityKunming
Period12/07/0815/07/08

Bibliographical note

This research is supported by support by the Natural Science Foundation of Hebei Province(F200800635), by the key project foundation of applied fundamental research of Hebei Province (08963522D), by the plan of 100 excellent innovative scientists of the first group in Education Department of Hebei Province, and the Scientific Research Foundation of Hebei Province (06213548). We also thank Junhai Zhai and Qiang He for their contribution.

Keywords

  • Convex Hull
  • Feature Selection
  • Linear Programming Problem

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