Fitting discrete Bayesian networks using soft-discretized data. Soft-discretization is based on mixture of normal distributions. Also implemented is a supervised Bayesian network learning employing Kullback-Leibler divergence. For more information see Balov (2013) <doi:10.1186/1755-8794-6-S3-S1>.
| Version: | 2.4.1 |
| Depends: | R (≥ 3.0.2) |
| Imports: | methods, stats, utils, graphics |
| Published: | 2019-04-30 |
| Author: | Nikolay Balov |
| Maintainer: | Nikolay Balov <nhbalov at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://www.biomedcentral.com/1755-8794/6/S3/S1 |
| NeedsCompilation: | yes |
| CRAN checks: | sdnet results |
| Reference manual: | sdnet.pdf |
| Package source: | sdnet_2.4.1.tar.gz |
| Windows binaries: | r-devel: sdnet_2.4.1.zip, r-devel-gcc8: sdnet_2.4.1.zip, r-release: sdnet_2.4.1.zip, r-oldrel: sdnet_2.4.1.zip |
| OS X binaries: | r-release: sdnet_2.4.1.tgz, r-oldrel: sdnet_2.4.1.tgz |
| Old sources: | sdnet archive |
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