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"""
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 graphical_lasso, GraphicalLasso, GraphicalLassoCV
from ._elliptic_envelope import EllipticEnvelope
__all__ = ['EllipticEnvelope',
'EmpiricalCovariance',
'GraphicalLasso',
'GraphicalLassoCV',
'LedoitWolf',
'MinCovDet',
'OAS',
'ShrunkCovariance',
'empirical_covariance',
'fast_mcd',
'graphical_lasso',
'ledoit_wolf',
'ledoit_wolf_shrinkage',
'log_likelihood',
'oas',
'shrunk_covariance']
|
