c3f2b4bf2f
* fixed all.equal(), it did not work as expected on networks
that were idetical save for the order of nodes or arcs.
* added a "moral" argument to cpdag() and vstructs() to make
those functions follow the different definitions of v-structure.
* added support for graphs with 1 and 2 nodes.
* fixed cpquery() handling of TRUE (this time for real).
* handle more corner cases in dsep().
* added a BIC method for bn and bn.fit objects.
* added the semiparametric tests from Tsamardinos & Borboudakis
(thanks Maxime Gasse).
* added posterior probabilities to the predictions for
{naive,tree}.bayes() models.
* fixed buffer overflow in rbn() for discrete data.
20 lines
1.1 KiB
Text
20 lines
1.1 KiB
Text
Bayesian network structure learning (via constraint-based, score-based
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and hybrid algorithms), parameter learning (via ML and Bayesian
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estimators) and inference.
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This package implements the Grow-Shrink (GS) algorithm, the
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Incremental Association (IAMB) algorithm, the Interleaved-IAMB
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(Inter-IAMB) algorithm, the Fast-IAMB (Fast-IAMB) algorithm, the
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Max-Min Parents and Children (MMPC) algorithm, the Hiton-PC algorithm,
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the ARACNE and Chow-Liu algorithms, the Hill-Climbing (HC) greedy
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search algorithm, the Tabu Search (TABU) algorithm, the Max-Min
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Hill-Climbing (MMHC) algorithm and the two-stage Restricted
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Maximization (RSMAX2) algorithm for both discrete and Gaussian
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networks, along with many score functions and conditional independence
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tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN)
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classifiers are also implemented.
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Some utility functions (model comparison and manipulation, random
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data generation, arc orientation testing, simple and advanced plots)
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are included, as well as support for parameter estimation and
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inference, conditional probability queries and cross-validation.
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