Rule quality measures settings in a sequential covering rule induction algorithm - an empirical approach

Abstract

The paper presents the results of research related to the efficiency of the so called rule quality measures which are used to evaluate the quality of rules at each stage of the rule induction. The stages of rule growing and pruning were considered along with the issue of conflicts resolution which may occur during the classification. The work is the continuation of research on the efficiency of quality measures employed in sequential covering rule induction algorithm. In this paper we analyse only these quality measures (9 measures) which had been recognised as effective based on previously conducted research.