content: """
  The :mod:`sklearn.covariance` module includes methods and algorithms to
  robustly estimate the covariance of features given a set of points. The
  precision matrix defined as the inverse of the covariance is also estimated.
  Covariance estimation is closely related to the theory of Gaussian Graphical
  Models.
  """
  
  from .empirical_covariance_ import empirical_covariance, EmpiricalCovariance, \
      log_likelihood
  from .shrunk_covariance_ import shrunk_covariance, ShrunkCovariance, \
      ledoit_wolf, ledoit_wolf_shrinkage, LedoitWolf, oas, OAS
  from .robust_covariance import fast_mcd, MinCovDet
  from .graph_lasso_ import graph_lasso, GraphLasso, GraphLassoCV
  from .outlier_detection import EllipticEnvelope, EllipticEnvelop
  
  __all__ = ['EllipticEnvelop',
             'EllipticEnvelope',
             'EmpiricalCovariance',
             'GraphLasso',
             'GraphLassoCV',
             'LedoitWolf',
             'MinCovDet',
             'OAS',
             'ShrunkCovariance',
             'empirical_covariance',
             'fast_mcd',
             'graph_lasso',
             'ledoit_wolf',
             'ledoit_wolf_shrinkage',
             'log_likelihood',
             'oas',
             'shrunk_covariance']
  