robust_covariance.py 文件源码

def correct_covariance(self, data):
        """Apply a correction to raw Minimum Covariance Determinant estimates.

        Correction using the empirical correction factor suggested
        by Rousseeuw and Van Driessen in [Rouseeuw1984]_.

        Parameters
        ----------
        data : array-like, shape (n_samples, n_features)
            The data matrix, with p features and n samples.
            The data set must be the one which was used to compute
            the raw estimates.

        Returns
        -------
        covariance_corrected : array-like, shape (n_features, n_features)
            Corrected robust covariance estimate.

        """
        correction = np.median(self.dist_) / chi2(data.shape[1]).isf(0.5)
        covariance_corrected = self.raw_covariance_ * correction
        self.dist_ /= correction
        return covariance_corrected