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PCP

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

Last updated 16 Mar, 2005


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1.2

1.2 beta released 2005-02-27

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