bnlearn_mmhc
MMHC
Package |
|
Version |
4.8.3 |
Language |
|
Docs |
|
Paper |
Tsamardinos et al.[1] |
Graph type |
|
Docker |
|
Module folder |
Description
Max-min hill-climbing (MMHC) is a hybrid method which first estimates the skeleton of a DAG using an algorithm called Max-Min Parents and Children and then performs a greedy hill-climbing search to orient the edges with respect to a Bayesian score. It is a popular approach used as standard benchmark and also well suited for high- dimensional domains.
Example JSON
[
{
"id": "mmhc-bde-mi",
"alpha": [
0.01,
0.05,
0.1
],
"test": "mi",
"score": "bde",
"iss": 0.1,
"issmu": 1,
"issw": null,
"l": 5,
"k": 1,
"prior": "uniform",
"beta": 1,
"timeout": null
},
{
"id": "mmhc-bge-zf",
"alpha": [
0.001,
0.01,
0.05,
0.1
],
"score": "bge",
"test": "zf",
"iss": 1,
"issmu": 1,
"issw": null,
"l": 5,
"k": 1,
"prior": "uniform",
"beta": null,
"timeout": null
}
]