Characterizations of nearest and farthest neighbor algorithms by clustering admissibility conditions Article

Chen, Z, Van Ness, J. (1998). Characterizations of nearest and farthest neighbor algorithms by clustering admissibility conditions . Pattern Recognition, 31(10), 1573-1578. 10.1016/S0031-3203(98)00002-8

cited authors

  • Chen, Z; Van Ness, J

abstract

  • Monotone admissibility for clustering algorithms was introduced in Fisher and Van Ness [Biometrika 58, 91-104 (1971)]. The present paper discusses monotone admissibility for a broad class of clustering algorithms called the Lance and Williams algorithms. Necessary and sufficient conditions for Lance and Williams algorithms to be monotone admissible are discussed here. It is shown that the only such algorithms which are monotone admissible are nearest neighbor and farthest neighbor. © 1998 Published by Elsevier Ltd on behalf of the Pattern Recognition Society. All rights reserved.

authors

publication date

  • January 1, 1998

published in

Digital Object Identifier (DOI)

start page

  • 1573

end page

  • 1578

volume

  • 31

issue

  • 10