sklearn.covariance.ledoit_wolf(X, assume_centered=False, block_size=1000)
[source]
Estimates the shrunk LedoitWolf covariance matrix.
Read more in the User Guide.
Parameters: 


Returns: 

The regularized (shrunk) covariance is:
(1  shrinkage) * cov + shrinkage * mu * np.identity(n_features)
where mu = trace(cov) / n_features
sklearn.covariance.ledoit_wolf
© 2007–2018 The scikitlearn developers
Licensed under the 3clause BSD License.
http://scikitlearn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf.html