Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks
Overview
Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) arXiv:1403.2310.
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- RR 4.4.0 released · 2024-04-24
- archivedRemoved from CRAN2024-04-12requires archived package 'sparsebnUtils'
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.0.72020-03-12 · diff ↗
- 0.0.62019-12-23 · diff ↗
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.0.52017-09-10 · diff ↗
- 0.0.42017-04-28 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 0.0.3
- 0.0.22016-11-23 · diff ↗
- 0.0.12016-08-11
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- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-08-11
- Total releases
- 7 / 10 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.2.3
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