pgmpy.example_models.load_model

pgmpy.example_models.load_model(name: str)

Loads an example model by name.

To find all available example models, use the list_models() function.

Parameters:

namestr

Name of the example model to load.

Returns:

model: pgmpy.base.DAG or pgmpy.models.DiscreteBayesianNetwork or pgmpy.models.LinearGaussianBayesianNetwork or

pgmpy.models.FunctionalBayesianNetwork

The loaded example model.

Examples

# Loading a discrete Bayesian network with parameters.

>>> from pgmpy.example_models import load_model
>>> model = load_model("bnlearn/alarm")
>>> print(model)
DiscreteBayesianNetwork named 'unknown' with 37 nodes and 46 edges
>>> len(model.nodes())
37
>>> model.get_cpds("HISTORY")
<TabularCPD representing P(HISTORY:2 | LVFAILURE:2) at 0x7d4527a84230>

# Loading a DAG without parameters.

>>> model = load_model("dagitty/acid_1996")
>>> print(model)
DAG with 18 nodes and 22 edges
>>> len(model.nodes())
18

# Loading a continuous Bayesian network with parameters.

>>> model = load_model("bnlearn/arth150")
>>> print(model)
LinearGaussianBayesianNetwork with 107 nodes and 150 edges

# Loading a bnRep discrete Bayesian network.

>>> model = load_model("bnrep/asia")
>>> print(model)
DiscreteBayesianNetwork named 'unknown' with 8 nodes and 8 edges