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MicroArray Gene-expression-based Program In Error rate estimation

Bioconductor version: Development (3.20)

Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes.

Author: Camille Maumet <Rmagpie at>, with contributions from C. Ambroise J. Zhu

Maintainer: Camille Maumet <Rmagpie at>

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biocViews Classification, Microarray, Software
Version 1.61.0
In Bioconductor since BioC 2.4 (R-2.9) (15 years)
License GPL (>= 3)
Depends R (>= 2.6.1), Biobase(>= 2.5.5)
Imports Biobase(>= 2.5.5), e1071, graphics, grDevices, kernlab, methods, pamr, stats, utils
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