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local discovery algorithms {bnlearn} | R Documentation |

## Local discovery structure learning algorithms

### Description

ARACNE and Chow-Liu learn simple graphs structures from data using pairwise mutual information coefficients.

### Usage

aracne(x, whitelist = NULL, blacklist = NULL, mi = NULL, debug = FALSE) chow.liu(x, whitelist = NULL, blacklist = NULL, mi = NULL, debug = FALSE)

### Arguments

`x` |
a data frame containing the variables in the model. |

`whitelist` |
a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs to be included in the graph. |

`blacklist` |
a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs not to be included in the graph. |

`mi` |
a character string, the estimator used for the pairwise (i.e. unconditional) mutual information
coefficients in the ARACNE and Chow-Liu algorithms. Possible values are |

`debug` |
a boolean value. If |

### Value

An object of class `bn`

. See `bn-class`

for details.

### Author(s)

Marco Scutari

### References

Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, Califano A (2006). "ARACNE: An
Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context". *BMC
Bioinformatics*, **7**(Suppl 1):S7.

### See Also

constraint-based algorithms, score-based algorithms, hybrid algorithms.

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