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PCP

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PCP

http://pcp.sourceforge.net/
PCP (Pattern Classification Program) is an machine learning program for supervised and unsupervised classification of patterns. It runs in interactive and batch modes, and implements the following machine learning algorithms and methods:
- k-means clustering
- Fisher's linear discriminant
- Singular Value Decomposition
- Principal Component Analysis
- feature subset selection
- Bayes error estimation
- parametric classifiers (linear and quadratic)
- pseudo-inverse linear discriminant
- k-Nearest Neighbor method
- neural networks
- Support Vector Machine algorithm
- cross-validation
- bagging (committee) classification


Download

Download External-link-icon.png version 1.2 (beta)
released on 27 February 2005

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Licensing

LicenseVerified byVerified onNotes
X11Janet Casey16 March 2005



Leaders and contributors

Contact(s)Role
"Email ljubomir@sfsu.edu" Ljubomir Buturovic Maintainer


Resources and communication

Audience Resource type URI
Bug Tracking,Developer,Support E-mail mailto:ljubomir@sfsu.edu


Software prerequisites

This entry (in part or in whole) was last reviewed on 16 March 2005.



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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”.

The copyright and license notices on this page only apply to the text on this page. Any software or copyright-licenses or other similar notices described in this text has its own copyright notice and license, which can usually be found in the distribution or license text itself.


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