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)¶