Package: sbfc 1.0.3

sbfc: Selective Bayesian Forest Classifier

An MCMC algorithm for simultaneous feature selection and classification, and visualization of the selected features and feature interactions. An implementation of SBFC by Krakovna, Du and Liu (2015), <arxiv:1506.02371>.

Authors:Viktoriya Krakovna

sbfc_1.0.3.tar.gz
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sbfc.pdf |sbfc.html
sbfc/json (API)

# Install 'sbfc' in R:
install.packages('sbfc', repos = c('https://vkrakovna.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/vkrakovna/sbfc/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • corral_augmented - Augmented corral data set: synthetic data with correlated attributes augmented with noise features
  • heart - Heart disease data set: disease outcomes given health attributes
  • madelon - Madelon data set: synthetic data from NIPS 2003 feature selection challenge

On CRAN:

1.00 score 4 scripts 185 downloads 7 exports 69 dependencies

Last updated 3 years agofrom:50f4f24b6f. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 21 2024
R-4.5-win-x86_64OKOct 21 2024
R-4.5-linux-x86_64OKOct 21 2024
R-4.4-win-x86_64OKOct 21 2024
R-4.4-mac-x86_64OKOct 21 2024
R-4.4-mac-aarch64OKOct 21 2024
R-4.3-win-x86_64OKOct 21 2024
R-4.3-mac-x86_64OKOct 21 2024
R-4.3-mac-aarch64OKOct 21 2024

Exports:data_discedge_density_plotlogposterior_plotsbfcsbfc_graphsignal_size_plotsignal_var_proportion

Dependencies:base64encbitbit64bslibcachemclicliprcolorspacecpp11crayonDiagrammeRdigestdiscretizationdplyrevaluatefansifarverfastmapfontawesomefsgenericsgluehighrhmshtmltoolshtmlwidgetsigraphjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimemunsellpillarpkgconfigprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppRcppArmadilloreadrrlangrmarkdownrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml