45 lines
1.1 KiB
Python
45 lines
1.1 KiB
Python
"""
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The :mod:`sklearn.covariance` module includes methods and algorithms to
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robustly estimate the covariance of features given a set of points. The
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precision matrix defined as the inverse of the covariance is also estimated.
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Covariance estimation is closely related to the theory of Gaussian Graphical
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Models.
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"""
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from ._elliptic_envelope import EllipticEnvelope
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from ._empirical_covariance import (
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EmpiricalCovariance,
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empirical_covariance,
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log_likelihood,
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)
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from ._graph_lasso import GraphicalLasso, GraphicalLassoCV, graphical_lasso
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from ._robust_covariance import MinCovDet, fast_mcd
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from ._shrunk_covariance import (
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OAS,
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LedoitWolf,
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ShrunkCovariance,
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ledoit_wolf,
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ledoit_wolf_shrinkage,
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oas,
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shrunk_covariance,
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)
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__all__ = [
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"EllipticEnvelope",
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"EmpiricalCovariance",
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"GraphicalLasso",
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"GraphicalLassoCV",
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"LedoitWolf",
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"MinCovDet",
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"OAS",
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"ShrunkCovariance",
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"empirical_covariance",
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"fast_mcd",
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"graphical_lasso",
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"ledoit_wolf",
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"ledoit_wolf_shrinkage",
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"log_likelihood",
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"oas",
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"shrunk_covariance",
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]
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