-
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
sklearn.covariance.shrunk_covariance()
2017-01-15 04:25:35
Please login to continue.