IAMB (bnlearn)

Module name	bnlearn_iamb
Package	bnlearn
Version	4.8.3
Language	R
Docs	here
Paper	Tsamardinos et al.[1]
Graph type	DAG
MCMC	No
Edge constraints	Yes
Data type	C, D, M
Data missingness
Intervention type
Docker	bpimages/bnlearn:4.8.3

Incremental Association Markov Blanket

Abstract: This paper presents a number of new algorithms for discovering the Markov Blanket of a target variable T from training data. The Markov Blanket can be used for variable selection for classification, for causal discovery, and for Bayesian Network learning. We introduce a low-order polynomial algorithm and several variants that soundly induce the Markov Blanket under certain broad conditions in datasets with thousands of variables and compare them to other state-of-the-art local and global methods with excellent results.

Some fields described

edgeConstraints Name of the JSON file containing background knowledge

Example JSON

[
  {
    "id": "iamb-zf",
    "alpha": [
      0.01,
      0.05
    ],
    "test": "zf",
    "B": null,
    "maxsx": null,
    "debug": false,
    "undirected": false,
    "timeout": null,
    "edgeConstraints": "edgeConstraints.json"
  },
  {
    "id": "iamb-mi",
    "alpha": [
      0.01,
      0.05
    ],
    "test": "mi",
    "B": null,
    "maxsx": null,
    "debug": false,
    "undirected": false,
    "timeout": null,
    "edgeConstraints": "edgeConstraints.json"
  }
]