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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.
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Package details |
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| Author | Eleni Chatzimichali <ea.chatzimichali@gmail.com> and Conrad Bessant <c.bessant@qmul.ac.uk> |
| Maintainer | Eleni Chatzimichali <ea.chatzimichali@gmail.com> |
| License | GPL (>= 2) |
| Version | 0.1-2 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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