Package: classyfire
Type: Package
Title: Robust multivariate classification using highly optimised SVM
        ensembles
Version: 0.1-2
Date: 2015-01-11
Author: Eleni Chatzimichali <ea.chatzimichali@gmail.com> and Conrad Bessant <c.bessant@qmul.ac.uk>
Maintainer: Eleni Chatzimichali <ea.chatzimichali@gmail.com>
Description: A collection of functions for the creation and application of highly optimised, robustly evaluated ensembles of support vector machines (SVMs). The package takes care of training individual SVM classifiers using a fast parallel heuristic algorithm, and combines individual classifiers into ensembles. Robust metrics of classification performance are offered by bootstrap resampling and permutation testing. 
License: GPL (>= 2)
Depends: R (>= 3.0.0), snowfall (>= 1.84-6), e1071 (>= 1.6-3), boot (>=
        1.3-11), neldermead (>= 1.0-9)
Imports: ggplot2 (>= 1.0-0), optimbase (>= 1.0-9)
Suggests: RUnit, knitr
VignetteBuilder: knitr
BugReports: https://github.com/eaHat/classyfire/issues
Packaged: 2015-01-11 16:16:53 UTC; elenachatzimichali
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-01-12 01:08:41
