sklearn.covariance.empirical_covariance

sklearn.covariance.empirical_covariance(X, assume_centered=False)

Computes the Maximum likelihood covariance estimator

Parameters:

X : ndarray, shape (n_samples, n_features)

Data from which to compute the covariance estimate

assume_centered : Boolean

If True, data are not centered before computation. Useful when working with data whose mean is almost, but not exactly zero. If False, data are centered before computation.

Returns:

covariance : 2D ndarray, shape (n_features, n_features)

Empirical covariance (Maximum Likelihood Estimator).

Examples using sklearn.covariance.empirical_covariance

Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood