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.

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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