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. Availability and implementation: ClassifyR is implemented in R and can be obtained from the Bioconductor project: http://bioconductor.org/packages/release/bioc/html/ClassifyR.html.
Original language | English |
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Pages (from-to) | 1851-1853 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 31 |
Issue number | 11 |
DOIs | |
Publication status | Published - 1 Jun 2015 |
Externally published | Yes |