Published October 8, 2024
| Version 0.9.0
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Learning Bayesian Networks with the bnlearn Python Package.
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Description
- Lingam methods (Direct and ICA) are implemented to model datasets with continuous variables (without discretizing). See docs here. #36
- Plotting is now possible using Graphviz which creates more clear figures. See docs here.
- For Constraint-based (PC), CII 9 tests are included and the alpha can be set.
- Parameter showfig and visible is available now for plotting #103
- Dynamic Bayesian Network (DBN) implemented. #100. See docs [here] (https://erdogant.github.io/bnlearn/pages/html/bnlearn.bnlearn.html#bnlearn.bnlearn.make_DAG) and here.
- Impute functionality implemented in case of missing values. #81 See docs over here.
- Updated docstrings and sphinx documentation pages.
- Created a logo! :-)
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Files
erdogant/bnlearn-0.9.0.zip
Files
(34.9 MB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/erdogant/bnlearn/tree/0.9.0 (URL)