Heuristic approximation methods for principal points for binary distributions

Haruka Yamashita, Hideo Suzuki

研究成果: Article

3 引用 (Scopus)

抜粋

The analysis of binary (0 or 1) data requires an analysis method whose objects are realizations. Yamashita and Suzuki (to appear) proposed principal points for binary distributions based on the concept of principal points, defined by Flury (1990). Ideally, when we search for the binary principal points, all combinations of the k-principal points should be considered; however, this problem cannot be solved in a straightforward manner because the number of combinations increases exponentially when the number of the variables increases. In this paper, we propose three heuristic methods for approximating principal points for binary distributions. The results indicate that our method enables us to find approximated principal points and summarize a binary distribution using the points.

元の言語English
ページ(範囲)131-141
ページ数11
ジャーナルJournal of Japan Industrial Management Association
65
発行部数2
出版物ステータスPublished - 2014
外部発表Yes

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Applied Mathematics
  • Management Science and Operations Research
  • Strategy and Management

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