sf_kmeans.py 文件源码

def _center_mahalanobis(self, data):
        """
        Finds a point that is in the center of the data using Mahalanobis distance.

        Parameters
        ----------
        data: input data as numpy array

        Returns
        -------
        mean: numpy array
        """
        distances = cdist(data, data, metric='mahalanobis', VI=self._inv_covar_matrices)
        sum_distances = np.sum(distances, axis=0)
        center_idx = np.argmin(sum_distances)
        return data[center_idx]