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scikits.learn.covariance.ShrunkCovariance

class scikits.learn.covariance.ShrunkCovariance(store_covariance=True, shrinkage=None)

Covariance estimator with shrinkage

Parameters :

store_covariance : bool

Specify if the estimated covariance is stored

shrinkage : float

Shrinkage (in [0, 1])

Notes

The regularized covariance is given by

(1 - shrinkage)*cov
  • shrinkage*mu*np.identity(n_features)

where mu = trace(cov) / n_features

Attributes

covariance_ 2D ndarray, shape (n_features, n_features) Estimated covariance matrix (stored only is store_covariance is True)
precision_ 2D ndarray, shape (n_features, n_features) Estimated precision matrix

Methods

fit
log_likelihood
score
__init__(store_covariance=True, shrinkage=None)