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Pattern Classification Program

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Description du projet:

English:
(Dernière mise à jour 2009-06-12 15:46)

PCP (Pattern Classification Program) is a machine learning
program for supervised 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,
dimension reduction using 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 (SVM), model selection for SVM, cross-validation, and bagging
(committee)
classification.

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Japonais:
 
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