CAM-UV¶

class lingam.CAMUV(alpha=0.01, num_explanatory_vals=2)[source]¶

Implementation of CAM-UV Algorithm [1]

References

[1]	T.N.Maeda and S.Shimizu. Causal additive models with unobserved variables. In Proc. Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (UAI). PMLR 161:97-106, 2021.

__init__(alpha=0.01, num_explanatory_vals=2)[source]¶

Construct a CAM-UV model.

Parameters:	alpha (float, optional (default=0.01)) – Alpha level. num_explanatory_vals (int, optional (default=2)) – Maximum number of explanatory variables.

adjacency_matrix_¶

Estimated adjacency matrix.

Returns:	adjacency_matrix_ – The adjacency matrix B of fitted model, where n_features is the number of features.
Return type:	array-like, shape (n_features, n_features)