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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 ._elliptic_envelope import EllipticEnvelope
from ._empirical_covariance import (
EmpiricalCovariance,
empirical_covariance,
log_likelihood,
)
from ._graph_lasso import GraphicalLasso, GraphicalLassoCV, graphical_lasso
from ._robust_covariance import MinCovDet, fast_mcd
from ._shrunk_covariance import (
OAS,
LedoitWolf,
ShrunkCovariance,
ledoit_wolf,
ledoit_wolf_shrinkage,
oas,
shrunk_covariance,
)
__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",
]
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