sklearn.covariance.shrunk_covariance

sklearn.covariance.shrunk_covariance(emp_cov, shrinkage=0.1) [source]

Calculates a covariance matrix shrunk on the diagonal

Read more in the User Guide.

Parameters:	emp_cov : array-like, shape (n_features, n_features) Covariance matrix to be shrunk shrinkage : float, 0 <= shrinkage <= 1 Coefficient in the convex combination used for the computation of the shrunk estimate.
Returns:	shrunk_cov : array-like Shrunk covariance.

Notes

The regularized (shrunk) covariance is given by:

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

where mu = trace(cov) / n_features