16 lines
813 B
Plaintext
16 lines
813 B
Plaintext
Bayesian network structure learning, parameter learning and inference.
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This package implements constraint-based (GS, IAMB, Inter-IAMB,
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Fast-IAMB, MMPC, Hiton-PC), pairwise (ARACNE and Chow-Liu),
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score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC and
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RSMAX2) structure learning algorithms for discrete, Gaussian and
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conditional Gaussian networks, along with many score functions and
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conditional independence tests. The Naive Bayes and the Tree-Augmented
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Naive Bayes (TAN) 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 (maximum
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likelihood and Bayesian) and inference, conditional probability
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queries and cross-validation.
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