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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.
é   )Úempirical_covarianceÚEmpiricalCovarianceÚlog_likelihood)Úshrunk_covarianceÚShrunkCovarianceÚledoit_wolfÚledoit_wolf_shrinkageÚ
LedoitWolfÚoasÚOAS)Úfast_mcdÚ	MinCovDet)Úgraphical_lassoÚGraphicalLassoÚGraphicalLassoCV)ÚEllipticEnvelope)r   r   r   r   r
   r   r   r   r   r   r   r   r	   r   r   r   N)Ú__doc__Ú_empirical_covariancer   r   r   Ú_shrunk_covariancer   r   r   r	   r
   r   r   Ú_robust_covariancer   r   Ú_graph_lassor   r   r   Ú_elliptic_enveloper   Ú__all__© ó    úW/var/www/html/Sam_Eipo/venv/lib/python3.11/site-packages/sklearn/covariance/__init__.pyú<module>r      sú   ððð ðð ð ð ð ð ð ð ð ð ð
ð ð ð ð ð ð ð ð ð ð ð ð ð ð ð ð ð ð 4Ð 3Ð 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø KÐ KÐ KÐ KÐ KÐ KÐ KÐ KÐ KÐ KØ 0Ð 0Ð 0Ð 0Ð 0Ð 0ðð ð €€€r   