Bayesian kernel projection classifier is a nonlinear multicategory classifier which performs the classification of the projections of the data to the principal axes of the feature space. A Gibbs sampler is implemented to find the posterior distributions of the parameters.
| Version: | 1.0.1 |
| Depends: | R (≥ 2.10) |
| Imports: | kernlab |
| Published: | 2018-03-13 |
| Author: | K. Domijan |
| Maintainer: | K. Domijan <domijank at tcd.ie> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | BKPC results |
| Reference manual: | BKPC.pdf |
| Package source: | BKPC_1.0.1.tar.gz |
| Windows binaries: | r-devel: BKPC_1.0.1.zip, r-release: BKPC_1.0.1.zip, r-oldrel: BKPC_1.0.1.zip |
| macOS binaries: | r-release: BKPC_1.0.1.tgz, r-oldrel: BKPC_1.0.1.tgz |
| Old sources: | BKPC archive |
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