BKPC-package: Bayesian Kernel Projection Classifier

In BKPC: Bayesian Kernel Projection Classifier

Description

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. The main function for end users is bkpc.

Details

Package:	BKPC
Type:	Package
Version:	1.0
Date:	2016-02-27
License:	GPL-2

Author(s)

K. Domijan <[e-mail]>

References

Domijan K. and Wilson S. P.: Bayesian kernel projections for classification of high dimensional data. Statistics and Computing, 2011, Volume 21, Issue 2, pp 203-216

See Also

kernlab

BKPC documentation built on May 1, 2019, 9:10 p.m.