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bsnsing
View on CRAN: Click
here
Download and install bsnsing package within the R console
Install from CRAN:
install.packages("bsnsing")
Install from Github:
library("remotes")
install_github("cran/bsnsing") Install by package version:
library("remotes")
install_version("bsnsing", "1.0.1") Attach the package and use:
library("bsnsing")
Maintained by
Yanchao Liu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-07-03
Latest Update: 2022-07-03
Description:
Functions for training an optimal decision tree classifier, making predictions and generating latex code for plotting. Works for two-class and multi-class classification problems. The algorithm seeks the optimal Boolean rule consisting of multiple variables to split a node, resulting in shorter trees. Use bsnsing() to build a tree, predict() to make predictions and plot() to plot the tree into latex and PDF. See Yanchao Liu (2022) for technical details. Source code and more data sets are at .
How to cite:
Yanchao Liu (2022). bsnsing: Build Decision Trees with Optimal Multivariate Splits. R package version 1.0.1, https://cran.r-project.org/web/packages/bsnsing. Accessed 06 Aug. 2026.
Previous versions and publish date:
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Other R packages that bsnsing depends,
imports, suggests or enhances
Complete documentation for bsnsing
Functions, R codes and Examples using
the bsnsing R package
Some associated functions: BreastCancer . GlaucomaMVF . ROC_func . auto . binarize.factor . binarize.numeric . binarize . binarize.y . bscontrol . bslearn . bsnsing-package . bsnsing.default . bsnsing.formula . bsnsing . import_external_rules . iris . mbsnsing-class . plot.bsnsing . plot.mbsnsing . predict.bsnsing . predict.mbsnsing . print.bscontrol . print.bsnsing . print.mbsnsing . print.summary.bsnsing . print.summary.mbsnsing . rcpp_bslearn . summary.bsnsing . summary.mbsnsing .
Some associated R codes: RcppExports.R . bsnsing.R . data.R . Full bsnsing package functions and examples
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