A Study on the Methods of Heuristic Approximation for Principal Points of Binary Data  

Oleh:

Yamashita, Haruka ; Suzuki, Hideo

Jenis: Article from Proceeding
Dalam koleksi: Asian Network for Quality (ANQ) Congress 2011, Ho Chi Minh City, Vietnam, 27-30 September 2011, page 1-11.
Topik: Principal Points; Binary data; Heuristic approximation method; k-means method; Empirical distribution
Fulltext: JP01-P_Yamashita_Fullpaper.pdf (203.51KB)

Isi artikel

In the analysis of binary (0 or 1) data, the analysis method whose objects are realizations should be required. Yamashita and Suzuki (2010) proposed Principal Points for binary data based on the concept of Principal Points, defined by Flury (1990). Ideally, when the Principal Points for binary data are sought, all combinations of k-Principal Points should be considered; however, this problem cannot be solved in a straightforward manner due to the fact that it is NP-hard. In this paper, we propose two heuristic methods for approximating Principal Points of binary data. It enables us to reduce the computational effort significantly.

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