classyfire: Robust multivariate classification using highly optimised SVM ensembles

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.

Install the latest version of this package by entering the following in R:
install.packages("classyfire")
AuthorEleni Chatzimichali <ea.chatzimichali@gmail.com> and Conrad Bessant <c.bessant@qmul.ac.uk>
Date of publication2015-01-12 01:08:41
MaintainerEleni Chatzimichali <ea.chatzimichali@gmail.com>
LicenseGPL (>= 2)
Version0.1-2

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Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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