To understand data from as many perspectives as possible,
one approach is to acquire all different individual classifiers.
However, this is not feasible. A better way might
be to heuristically compute the individual classifiers which
satisfy some constraints. For example, given a training data
set and some constraints such as training error threshold,
the goal is to search a set of decision trees satisfying