Allows the user to learn Bayesian networks from datasets containing thousands of variables. It focuses on score-based learning, mainly the 'BIC' and the 'BDeu' score functions. It provides state-of-the-art algorithms for the following tasks: (1) parent set identification - Mauro Scanagatta (2015) <http://papers.nips.cc/paper/5803-learning-bayesian-networks-with-thousands-of-variables>; (2) general structure optimization - Mauro Scanagatta (2018) <doi:10.1007/s10994-018-5701-9>, Mauro Scanagatta (2018) <http://proceedings.mlr.press/v73/scanagatta17a.html>; (3) bounded treewidth structure optimization - Mauro Scanagatta (2016) <http://papers.nips.cc/paper/6232-learning-treewidth-bounded-bayesian-networks-with-thousands-of-variables>; (4) structure learning on incomplete data sets - Mauro Scanagatta (2018) <doi:10.1016/j.ijar.2018.02.004>. Distributed under the LGPL-3 by IDSIA.
| Version: | 1.1 |
| Depends: | R (≥ 3.0.0) |
| Imports: | foreign, bnlearn (≥ 4.0) |
| Published: | 2019-02-27 |
| Author: | Mauro Scanagatta [aut, cre] |
| Maintainer: | Mauro Scanagatta <mauro at idsia.ch> |
| License: | LGPL-3 |
| NeedsCompilation: | no |
| SystemRequirements: | Java (>= 1.5) |
| Materials: | README INSTALL |
| CRAN checks: | r.blip results |
| Reference manual: | r.blip.pdf |
| Package source: | r.blip_1.1.tar.gz |
| Windows binaries: | r-devel: r.blip_1.1.zip, r-release: r.blip_1.1.zip, r-oldrel: r.blip_1.1.zip |
| macOS binaries: | r-release: r.blip_1.1.tgz, r-oldrel: r.blip_1.1.tgz |
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