StructureScore

class pgmpy.metrics.StructureScore(scoring_method=None)

Bases: _BaseUnsupervisedMetric

Uses the standard model scoring methods to give a score for each structure. The score doesn’t have very straight forward interpretability but can be used to compare different models. A higher score represents a better fit. This method only needs the model structure to compute the score and parameters aren’t required.

Parameters:

scoring_method: str

Options are: k2, bdeu, bds, bic-d, aic-d, ll-g, aic-g, bic-g, ll-cg, aic-cg, bic-cg

Returns:

Model score: float

A score value for the model.

Examples

>>> from pgmpy.example_models import load_model
>>> from pgmpy.metrics import StructureScore
>>> model = load_model("bnlearn/alarm")
>>> data = model.simulate(int(1e4), seed=42)
>>> scorer = StructureScore(scoring_method="bic-d")
>>> scorer(X=data, causal_graph=model)
np.float64(-106325.43476616534)