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sklearn.covariance.shrunk_covariance(emp_cov, shrinkage=0.1)
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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
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- shrinkage*mu*np.identity(n_features)
where mu = trace(cov) / n_features
sklearn.covariance.shrunk_covariance()
2017-01-15 04:25:35
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