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r-ccdralgorithm

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Implementation of the CCDr (Concave penalized Coordinate Descent with reparametrization) structure learning algorithm as described in Aragam and Zhou (2015) <http://www.jmlr.org/papers/v16/aragam15a.html>. This is a fast, score-based method for learning Bayesian networks that uses sparse regularization and block-cyclic coordinate descent.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-ccdralgorithm

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Summary

Implementation of the CCDr (Concave penalized Coordinate Descent with reparametrization) structure learning algorithm as described in Aragam and Zhou (2015) <http://www.jmlr.org/papers/v16/aragam15a.html>. This is a fast, score-based method for learning Bayesian networks that uses sparse regularization and block-cyclic coordinate descent.

Last Updated

Apr 12, 2022 at 07:20

License

GPL-2.0-or-later

Total Downloads

68.0K

Supported Platforms

win-64
macOS-64
linux-64