Autoclass

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Autoclass

http://ic-www.arc.nasa.gov/ic/projects/bayes-group/autoclass/
Automatic classification or clustering

AutoClass solves the problem of automatic discovery of classes in data (sometimes called clustering or unsupervised learning), as distinct from the generation of class descriptions from labeled examples (called supervised learning). It aims to discover the 'natural' classes in the data. AutoClass is applicable to observations of things that can be described by a set of attributes, without referring to other things. The data values corresponding to each attribute are limited to be either numbers or the elements of a fixed set of symbols. With numeric data, a measurement error must be provided.

Documentation

User intro included; user reference manual included


Download

Download version 3.3.6 (stable)
released on 1 September 2009

Categories




Licensing

LicenseVerified byVerified onNotes
PublicDomainJanet Casey31 January 2001



Leaders and contributors

Contact(s)Role
James R. Van Zandt Maintainer


Resources and communication

Software prerequisites

KindDescription
Required to useglibc

This entry (in part or in whole) was last reviewed on 22 December 2016.



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