© 1973 by British Computer Society
An information measure for hierarchic classification
Department of Information Science, Monash University, Clayton, Victoria, Australia
The information measure has been developed as a criterion of merit for intrinsic classifications. The information measure for non-hierarchic classifications has been described previously and a program developed which searched for that classification optimising the information measure. However, hierarchic classifications are often of practical importance and this paper develops the information measure for hierarchic classifications. Two algorithms are outlined for generating hierarchic classifications which minimise the information measure. One of these has been programmed and first tests show a good agreement with conventional taxonomy.
Received June 1972.
* Department of Information Science, Monash University, Clayton, Victoria, 3168, Australia
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
D. L. Dowe, S. Gardner, and G. Oppy Bayes not Bust! Why Simplicity is no Problem for Bayesians Brit J Philos Sci, December 1, 2007; 58(4): 709 - 754. [Abstract] [Full Text] [PDF] |
||||
