The methods for approximation of principal points for binary distributions on the basis of submodularity

Haruka Yamashita, Hideo Suzuki

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Principal points for binary distributions are able to be defined based on Flurys principal points (1990). However, finding principal points for binary distributions is hard in a straightforward manner. In this article, a method for approximating principal points for binary distributions is proposed by formulating it as an uncapacitated location problem. Moreover, it is shown that the problem of finding principal points can be solved with the aid of submodular functions. It leads to a solution whose value is at least (1 - 1/e) times the optimal value.

Original languageEnglish
Pages (from-to)2291-2309
Number of pages19
JournalCommunications in Statistics - Theory and Methods
Volume44
Issue number11
DOIs
Publication statusPublished - 2015 Jun 3

Keywords

  • Clustering
  • Data analysis
  • Multivariate binary distribution
  • Uncapacitated location problem

ASJC Scopus subject areas

  • Statistics and Probability

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