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.
| Version: |
0.1-0 |
| 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) |
| Published: |
2014-09-05 |
| Author: |
Eleni Chatzimichali and Conrad Bessant |
| Maintainer: |
Eleni Chatzimichali <ea.chatzimichali at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
classyfire results |