^MML^ ^Structured^ ^Mixtures^ >factor-snob>
SNOB is written in Fortran 77, and more recently C, and is available from:
[Snob][2003], [Snob][2001].
(NB. So called "vanilla" Snob only implements multi- state and normal dist'ns as of '04.)


SNOB is a computer program for unsupervised classification of multivariate data. The classification problem is sometimes called clustering, mixture modelling or numerical taxonomy. SNOB uses the Minimum [Message|Description] Length [Encoding] (MML|MDL) principle to decide upon the best classification of the data. MML encoding is a realisation of Ockham's razor.

SNOB is very efficient and can classify many tens of thousands of "things" quickly, where each thing can have tens of "attributes" (variables). An attribute can be continuous (real-valued) or discrete (multi-state).

A "class" is defined by distributions on one or more, but not necessarily all, attributes. The number of classes, the classes, their defining attributes and distributions, and class memberships are all inferred by SNOB.

Selected Bibliography:

C. S. Wallace. Vanilla Snob. 2002 [www]['02].
C. S. Wallace. Classification by Minimum-Message-Length Inference. Advances in Computing and Information - ICCI '90. Springer Verlag LNCS 468 pp.72-81 1990.
C. S. Wallace & P. R. Freeman. Estimation and Inference by Compact Encoding. J. R. Stat. Soc. B 49 pp.240-265 1987
D. M. Boulton & C. S. Wallace. An Information Measure for Hierarchic Classification. Computer Journal 16(3) pp.254-261 1973.
D. M. Boulton & C. S. Wallace. A Program for Numerical Classification. Computer Journal 13(1) pp.63-69 1970.
C. S. Wallace & D. M. Boulton. An Information Measure for Classification. Computer Journal 11 pp.185-195 1968.
L. Allison. Models for machine learning and data mining in functional programming. J. Functional Programming, 15(1), pp.15-32, Jan. 2005.
Includes the source code of the core expectation-maximization (EM) algorithm for clustering. Also see [I.I.].

Also see [Inductive Inference] for more on mixture models, [CSW's publications], and search for `Snob' in the [bibliography].

© L. Allison / 1994, 1999, 2000, 2001, 2002, 2003, 2005
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