  In this paper, we consider classes of decision tables with 0-1-decisions
closed relative to removal of attributes (columns) and changing decisions
assigned to rows. For tables from an arbitrary closed class, we study the
dependence of the minimum complexity of deterministic decision trees on various
parameters of the tables: the minimum complexity of a test, the complexity of
the set of attributes attached to columns, and the minimum complexity of a
strongly nondeterministic decision tree. We also study the dependence of the
minimum complexity of strongly nondeterministic decision trees on the
complexity of the set of attributes attached to columns. Note that a strongly
nondeterministic decision tree can be interpreted as a set of true decision
rules that cover all rows labeled with the decision 1.
