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conda-forge / packages / r-ccdralgorithm

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.

copied from cf-post-staging / r-ccdralgorithm
Type Size Name Uploaded Downloads Labels
conda 145.0 kB | osx-64/r-ccdralgorithm-0.0.6-r41hc4bb905_0.tar.bz2  3 years and 6 months ago 86 main
conda 146.8 kB | linux-64/r-ccdralgorithm-0.0.6-r41h7525677_0.tar.bz2  3 years and 6 months ago 2730 main
conda 146.5 kB | linux-64/r-ccdralgorithm-0.0.6-r40h7525677_0.tar.bz2  3 years and 6 months ago 2791 main

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