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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) <doi:10.48550/arXiv.2205.15263> for technical details. Source code and more data sets are at <https://github.com/profyliu/bsnsing/>.
| Version: | 1.0.1 |
| Imports: | methods, Rcpp (≥ 1.0.3) |
| LinkingTo: | Rcpp |
| Suggests: | C50, party, rpart, tree |
| Published: | 2022-07-03 |
| DOI: | 10.32614/CRAN.package.bsnsing |
| Author: | Yanchao Liu |
| Maintainer: | Yanchao Liu <yanchaoliu at wayne.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | bsnsing results |
| Reference manual: | bsnsing.pdf |
| Package source: | bsnsing_1.0.1.tar.gz |
| Windows binaries: | r-devel: bsnsing_1.0.1.zip, r-release: bsnsing_1.0.1.zip, r-oldrel: bsnsing_1.0.1.zip |
| macOS binaries: | r-release (arm64): bsnsing_1.0.1.tgz, r-oldrel (arm64): bsnsing_1.0.1.tgz, r-release (x86_64): bsnsing_1.0.1.tgz, r-oldrel (x86_64): bsnsing_1.0.1.tgz |
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