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