OCARA AS METHOD OF CLASSIFICATION AND ASSOCIATION RULES OBTAINING
DOI:
https://doi.org/10.62103/unilak.eajst.5.5.88Keywords:
class association rule, association rule, classification, data miningAbstract
This article focuses on how to integrate the two major data mining techniques namely, classification and
association rules to come up with An Optimal Class Association Rule Algorithm (OCARA) as Method of
Classification and Association Rules Obtaining. Classification and association rule mining algorithms are two
important aspects of datamining. Classification association rule mining algorithm is a promising approach for it
involves the use of association rule mining algorithm to discover classification rules.
OCARA inherits the strength of Classification and association rule mining algorithms. Because of this reason,
OCARA is a powerful algorithm when compared to either Classification or Association rule mining algorithms.
The reason for OCARA’s high accuracy is because of optimal association rule mining algorithm and the rule set
is sorted by priority of rules resulting into a more accurate classifier. Therefore, we can confidently say OCARA
is an accurate classifier and has better performance and is more efficient when compared with C4.5, CBA, and
RMR algorithm.