  In [1], a clustering algorithm was given to find the centers of clusters
quickly. However, the accuracy of this algorithm heavily depend on the
threshold value of d-c. Furthermore, [1] has not provided any efficient way to
select the threshold value of d-c, that is, one can have to estimate the value
of d_c depend on one's subjective experience. In this paper, based on the data
field [2], we propose a new way to automatically extract the threshold value of
d_c from the original data set by using the potential entropy of data field.
For any data set to be clustered, the most reasonable value of d_c can be
objectively calculated from the data set by using our proposed method. The same
experiments in [1] are redone with our proposed method on the same experimental
data set used in [1], the results of which shows that the problem to calculate
the threshold value of d_c in [1] has been solved by using our method.
