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bnlearn (version 0.7)

Bayesian network structure learning

Description

Bayesian network structure learning via constraint-based (also known as 'conditional independence') and score-based algorithms. This package implements the Grow-Shrink (GS) algorithm, the Incremental Association (IAMB) algorithm, the Interleaved-IAMB (Inter-IAMB) algorithm, the Fast-IAMB (Fast-IAMB) algorithm and the Hill-Climbing (HC) greedy search algorithm for both discrete and gaussian networks, along with many score functions and conditional independence tests. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing) are also included.

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Version

Install

install.packages('bnlearn')

Monthly Downloads

20,455

Version

0.7

License

GPL (>= 2)

Maintainer

Marco Scutari

Last Published

January 7th, 2025

Functions in bnlearn (0.7)

Hill-Climbing (HC) learning algorithm

Plot a Bayesian network

model string tools

Build a model string from a Bayesian network and vice versa

Grow-Shrink (GS) learning algorithm

snow integration

bnlearn - snow package integration

Compare two different Bayesian networks

graph generation tools

Generate an empty or random graph

Drop, add or set the direction of an arc

node ordering tools

Partial node ordering utilities

Synthetic (continuous) dataset to test learning algorithms

Fast Incremental Association (Fast-IAMB) learning algorithm

bnlearn-package

Bayesian network constraint-based structure learning.

Interleaved Incremental Association (Inter-IAMB) learning algorithm

Score of the Bayesian network

Utilities to manipulate graphs

Generate random data from a given Bayesian network

Synthetic (discrete) dataset to test learning algorithms

Incremental Association (IAMB) learning algorithm

choose.direction

Try to infer the direction of an undirected arc

The bn class structure