6.9.4. scikits.learn.covariance.ledoit_wolf¶
- scikits.learn.covariance.ledoit_wolf(X, return_shrinkage=False)¶
Estimates the shrunk Ledoit-Wolf covariance matrix.
Parameters : X: 2D ndarray, shape (n, p) :
The data matrix, with p features and n samples.
return_shrinkage: boolean, optional :
If return_shrinkage is True, the regularisation_factor is returned.
Returns : regularised_cov: 2D ndarray :
Regularized covariance
shrinkage: float :
Regularisation factor
Notes
The regularised covariance is:
(1 - shrinkage)*cov + shrinkage * mu * np.identity(n_features)
where mu = trace(cov) / n_features