  In classification problems, especially those that categorize data into a
large number of classes, the classes often naturally follow a hierarchical
structure. That is, some classes are likely to share similar structures and
features. Those characteristics can be captured by considering a hierarchical
relationship among the class labels. Here, we extend a recent simple
classification approach on binary data in order to efficiently classify
hierarchical data. In certain settings, specifically, when some classes are
significantly easier to identify than others, we showcase computational and
accuracy advantages.
