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Description

Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks.

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>.

discretecdAlgorithm

Build Status

An algorithm to learn structure of discrete Bayesian network, this package can deal with observational data, interventional data, or a mixture of both.

algorithm

  • cd.run is the main function to run coordinate descent algorithm. With the adaptive option, users may choose to use regular group lasso penalty, or adaptive group lasso penalty.
  • max_lambda is a function to calculate the maximum value of lambda that will penalized all edges to zero.
Metadata

Version

0.0.7

License

Unknown

Platforms (75)

    Darwin
    FreeBSD
    Genode
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    MMIXware
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