for accurate classifiers. Over the years, a number of associative classifiers based on positive
rules have been proposed in literature. The target of this paper is to improve classification
accuracy by using both negative and positive class association rules without sacrificing
performance. The generation of negative associations from datasets has been attacked from
different perspectives by various authors and this has proved to be a very computationally …