Package: BKPC 1.0.2
BKPC: Bayesian Kernel Projection Classifier
Bayesian kernel projection classifier (Domijan and Wilson,2011) <doi:10.1007/s11222-009-9161-8> 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.
Authors:
BKPC_1.0.2.tar.gz
BKPC_1.0.2.tar.gz(r-4.7-arm64)BKPC_1.0.2.tar.gz(r-4.7-x86_64)BKPC_1.0.2.tar.gz(r-4.6-arm64)BKPC_1.0.2.tar.gz(r-4.6-x86_64)
BKPC_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BKPC/json (API)
| # Install 'BKPC' in R: |
| install.packages('BKPC', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/domijan/bkpc/issues
Datasets:
- microarray - Microarray gene expression data
Last updated from:b1a10e2882. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 112 | ||
| linux-devel-x86_64 | OK | 110 | ||
| source / vignettes | OK | 145 | ||
| linux-release-arm64 | OK | 114 | ||
| linux-release-x86_64 | OK | 131 | ||
| wasm-release | OK | 96 |
Exports:bkpcgaussKernkPCAmarginalRelevance
Dependencies:kernlab
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Kernel Projection Classifier | BKPC-package BKPC |
| Bayesian Kernel Projection Classifier | bkpc bkpc.default bkpc.kern bkpc.kernelMatrix |
| Gaussian kernel | gaussKern |
| Kernel Principal Components Analysis | getPrincipalComponents kPCA kPCA.default kPCA.kern kPCA.kernelMatrix predict.kPCA |
| Feature Marginal Relevance | marginalRelevance |
| Microarray gene expression data | microarray |
| Plot bkpc Objects | plot.bkpc |
| Predict Method for Bayesian Kernel Projection Classifier | predict.bkpc predictMultinomSamples |
| Summary statistics for Markov Chain Monte Carlo chain from Bayesian Kernel Projection Classifier | summary.bkpc |
