  This article describes an action rule induction algorithm based on a
sequential covering approach. Two variants of the algorithm are presented. The
algorithm allows the action rule induction from a source and a target decision
class point of view. The application of rule quality measures enables the
induction of action rules that meet various quality criteria. The article also
presents a method for recommendation induction. The recommendations indicate
the actions to be taken to move a given test example, representing the source
class, to the target one. The recommendation method is based on a set of
induced action rules. The experimental part of the article presents the results
of the algorithm operation on sixteen data sets. As a result of the conducted
research the Ac-Rules package was made available.
