title: ClassifyR: an R package for performance assessment of classification with applications to transcriptomics.
abstract: Although a large collection of classification software packages exist in R, a new generic framework for linking custom classification functions with classification performance measures is needed. A generic classification framework has been designed and implemented as an R package in an object oriented style. Its design places emphasis on parallel processing, reproducibility and extensibility. Finally, a comprehensive set of performance measures are available to ease post-processing. Taken together, these important characteristics enable rapid and reproducible benchmarking of alternative classifiers.
  
  
  METHODS
  ClassifyR is implemented in R and can be obtained from the Bioconductor project: http://bioconductor.org/packages/release/bioc/html/ClassifyR.html.
authors: School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.
authors: Dario
authors: D
authors: Strbenac
authors: School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.
authors: Graham J
authors: GJ
authors: Mann
authors: School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.
authors: John T
authors: JT
authors: Ormerod
authors: School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.
authors: Jean Y H
authors: JY
authors: Yang
mesh_terms: D002965:Classification / Q000379:methods; D020869:Gene Expression Profiling; D006801:Humans; D012984:Software