depynd.markov_networks
¶
Module contents¶
-
depynd.markov_networks.
select
(X, method='skeptic', criterion='stars', lamb=None, verbose=False, return_lambda=False, **kwargs)¶ Learn the structure of Markov random field.
Parameters: - X (array-like, shape (n_samples, n_features)) – Observations of a set of random variables.
- method ({'glasso', 'skeptic', 'gsmn', 'iamb'}) – Method for structure learning.
- criterion ({'stars', 'none'}) – Criteria for selecting regularization parameter.
- lamb (float or array-like or None) – Candidates of regularization parameter.
- verbose (bool) – If True, the objective function is plotted for each regularization parameter.
- return_lambda (bool, default False) – If True, the selected regularization parameter will be returned.
- kwargs (dict) – Optional parameters for MI estimation.
Returns: adj – Estimated adjacency matrix of an MRF.
Return type: array, shape (n_features, n_features)
Methods¶
The select()
function supports the following methods:
- ‘glasso’:
depynd.markov_networks._glasso()
- ‘skeptic’:
depynd.markov_networks._skeptic()
- ‘gsmn’:
depynd.markov_networks._gsmn()
- ‘iamb’:
depynd.markov_networks._iamb()
Criteria¶
The select()
function supports the following criteria:
- ‘stars’:
depynd.markov_networks._stars()