Heuristic approximation methods for principal points for binary distributions

Haruka Yamashita, Hideo Suzuki

研究成果: Article査読

5 被引用数 (Scopus)


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.

ジャーナルJournal of Japan Industrial Management Association
出版ステータスPublished - 2014

ASJC Scopus subject areas

  • 戦略と経営
  • 経営科学およびオペレーションズ リサーチ
  • 産業および生産工学
  • 応用数学


「Heuristic approximation methods for principal points for binary distributions」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。