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venv/Lib/site-packages/sklearn/covariance/__init__.py

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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']