  This article offers a modification of Chow and Liu's learning algorithm in
the context of handwritten digit recognition. The modified algorithm directs
the user to group digits into several classes consisting of digits that are
hard to distinguish and then constructing an optimal conditional tree
representation for each class of digits instead of for each single digit as
done by Chow and Liu (1968). Advantages and extensions of the new method are
discussed. Related works of Wong and Wang (1977) and Wong and Poon (1989) which
offer a different entropy-based learning algorithm are shown to rest on
inappropriate assumptions.
