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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.


User intro included; user reference manual included


Download version 3.3.4 (stable)
released on 24 January 2002



LicenseVerified byVerified onNotes
PublicDomainJanet Casey31 January 2001

Leaders and contributors

James R. Van Zandt Maintainer

Resources and communication

Software prerequisites

Kind Description
Required to use glibc

This entry (in part or in whole) was last reviewed on 28 March 2003.


Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the page “GNU Free Documentation License”.

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