Abstract
We present RULES, a simple inductive learning algorithm for extracting
IF-THEN rules from a set of training examples. We also describe the
application of RULES to a range of problems, each involving a different
number of attributes, values, and classes. The results obtained demonstrate
that in spite of its simplicity RULES is at least comparable to other
inductive learning algorithms, if not more accurate and more general.
(Autor)