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Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC and RSMAX2) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries and cross-validation. Development snapshots with the latest bugfixes are available from <http://www.bnlearn.com>.

copied from cf-staging / r-bnlearn
  • License: GPL-2.0-or-later
  • Home: http://www.bnlearn.com/
  • 130226 total downloads
  • Last upload: 1 month and 22 days ago

Installers

Info: This package contains files in non-standard labels.
  • linux-64 v5.0.2
  • osx-64 v5.0.2
  • win-64 v5.0.2

conda install

To install this package run one of the following:
conda install conda-forge::r-bnlearn
conda install conda-forge/label/cf201901::r-bnlearn
conda install conda-forge/label/cf202003::r-bnlearn
conda install conda-forge/label/gcc7::r-bnlearn

Description


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