classyfire (0.1-2)

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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.

Maintainer: Eleni Chatzimichali
Author(s): Eleni Chatzimichali <> and Conrad Bessant <>

License: GPL (>= 2)

Uses: boot, e1071, ggplot2, neldermead, optimbase, snowfall, RUnit, knitr

Released about 5 years ago.

2 previous versions



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