BKPC: Bayesian Kernel Projection Classifier
Version 1.0

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.

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AuthorK. Domijan
Date of publication2016-02-27 14:35:00
MaintainerK. Domijan <domijank@tcd.ie>
LicenseGPL-2
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("BKPC")

Man pages

bkpc: Bayesian Kernel Projection Classifier
BKPC-package: Bayesian Kernel Projection Classifier
gaussKern: Gaussian kernel
kPCA: Kernel Principal Components Analysis
marginalRelevance: Marginal Relevance
microarray: Microarray gene expression data
plot.bkpc: Plot bkpc Objects
plot.marginalRelevance: Plot marginalRelevance Objects
predict.bkpc: Predict Method for Bayesian Kernel Projection Classifier
summary.bkpc: Summary statistics for Markov Chain Monte Carlo chain from...

Functions

BKPC Man page
BKPC-package Man page
bkpc Man page Source code
bkpc.default Man page Source code
bkpc.kern Man page Source code
bkpc.kernelMatrix Man page Source code
gaussKern Man page Source code
getPrincipalComponents Man page Source code
kPCA Man page Source code
kPCA.default Man page Source code
kPCA.kern Man page Source code
kPCA.kernelMatrix Man page Source code
marginalRelevance Man page Source code
microarray Man page
plot.bkpc Man page Source code
plot.marginalRelevance Man page Source code
predict.bkpc Man page Source code
predict.kPCA Man page Source code
predictMultinomSamples Man page Source code
summary.bkpc Man page Source code

Files

src
src/Makevars
src/matrices.h
src/getKPCs.c
src/rkern.c
src/matrices.c
src/gibbsBKPC.c
src/Makevars.win
NAMESPACE
data
data/microarray.rda
R
R/summary.bkpc.R
R/kPCA.kernelMatrix.R
R/bkpc.R
R/predict.bkpc.R
R/bkpc.kernelMatrix.R
R/predict.kPCA.R
R/gaussKern.R
R/plot.marginalRelevance.R
R/kPCA.default.R
R/predictMultinomSamples.R
R/bkpc.kern.R
R/bkpc.default.R
R/marginalRelevance.R
R/kPCA.kern.R
R/getPrincipalComponents.R
R/plot.bkpc.R
R/kPCA.R
MD5
DESCRIPTION
man
man/kPCA.Rd
man/bkpc.Rd
man/gaussKern.Rd
man/plot.marginalRelevance.Rd
man/plot.bkpc.Rd
man/summary.bkpc.Rd
man/BKPC-package.Rd
man/marginalRelevance.Rd
man/microarray.Rd
man/predict.bkpc.Rd
BKPC documentation built on May 19, 2017, 4:35 p.m.