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JUPYTER
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Jupyter notebooks for the Python version of GOBNILP
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At present the following notebooks are available.
Python notebooks
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Basic learning from continuous data
Basic learning from discrete data
Understanding Gobnilp's stages of learning
Computing local scores and solving with and without constraints
Using simple constraints
Learning Bayesian networks for a subset of variables
Learning multiple related Bayesian networks
Using a constraints file
Defining general MIP constraints in a constraints file
The pitfalls of learning with latent variables
R notebooks
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Calling gobnilp from R
Comparing bnlearn and gobnilp on bigger datasets