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A framework for two-class classification problems, with applications to differential variability and differential distribution testing.

Bioconductor version: 3.0

The software formalises a framework for classification in R. There are four stages. Data transformation, feature selection, and prediction. The requirements of variable types and names are fixed, but specialised variables for functions can also be provided. The classification framework is wrapped in a driver loop, that reproducibly does a couple of cross-validation schemes. Functions for differential expression, differential variability, and differential distribution are included. Additional functions may be developed by the user, if they have better performing methods.

Author: Dario Strbenac, John Ormerod, Graham Mann, Jean Yang

Maintainer: Dario Strbenac <dario.strbenac at>

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HTML R Script An Introduction to the ClassifyR Package
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biocViews Classification, Software, Survival
Version 1.0.18
In Bioconductor since BioC 3.0 (R-3.1)
License GPL-3
Depends R (>= 3.0.3), methods, Biobase, BiocParallel
Imports locfit, ROCR, grid
Suggests limma, edgeR, car, Rmixmod, ggplot2, gridExtra, BiocStyle, pamr, sparsediscrim, PoiClaClu, curatedOvarianData, parathyroidSE, knitr, klaR, gtable, scales
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