[MUD-Dev] AutoClass

[Ling Lo]

Oook, found something interesting, esp for those of you that have auditing
facilities in your mud:

http://ic-www.arc.nasa.gov/ic/projects/bayes-group/autoclass/

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In previous years, the Bayes group at Ames Research Center developed the
basic theory and associated algorithms for various kinds of general data
analysis techniques. Our earliest efforts were applied to the problem of
automatic classification of data. We implemented this theory in the
Autoclass series of programs. AutoClass takes a database of cases
described by a combination of real and discrete valued attributes, and
automatically finds the natural classes in that data. It does not need to
be told how many classes are present or what they look like -- it extracts
this information from the data itself. The classes are described
probabilistically, so that an object can have partial membership in the
different classes, and the class definitions can overlap. AutoClass
generates reports on the classes it has found at the end of its search.
AutoClass has been used and tested on many data sets, both within NASA and
by industry, academia and other agencies. These applications typically
find surprising classifications that show patterns in the data unknown to
the user. Examples include: discovery of new classes of infra-red stars in
the IRAS Low Resolution Spectral catalogue (see figure below; and see here
and here for more information), new classes of airports in a database of
all USA airports, discovery of classes of proteins, introns and other
patterns in DNA/protein sequence data, and others.
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This one looks like a tried and tested stylee.
--
  |   Ling Lo
_O_O_ kllo at iee.org




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