sklearn.covariance.ledoit_wolf(X, assume_centered=False, block_size=1000)

class sklearn.covariance.ShrunkCovariance(store_precision=True, assume_centered=False, shrinkage=0.1)

sklearn.covariance.shrunk_covariance(emp_cov, shrinkage=0.1)

class sklearn.covariance.EllipticEnvelope(store_precision=True, assume_centered=False, support_fraction=None, contamination=0.1

sklearn.covariance.graph_lasso(emp_cov, alpha, cov_init=None, mode='cd', tol=0.0001, enet_tol=0.0001, max_iter=100, verbose=False

class sklearn.covariance.GraphLassoCV(alphas=4, n_refinements=4, cv=None, tol=0.0001, enet_tol=0.0001, max_iter=100, mode='cd', n_jobs=1

class sklearn.covariance.EmpiricalCovariance(store_precision=True, assume_centered=False)

class sklearn.covariance.LedoitWolf(store_precision=True, assume_centered=False, block_size=1000)

class sklearn.covariance.MinCovDet(store_precision=True, assume_centered=False, support_fraction=None, random_state=None)

class sklearn.covariance.GraphLasso(alpha=0.01, mode='cd', tol=0.0001, enet_tol=0.0001, max_iter=100, verbose=False, assume_centered=False)