An approach to improve apriori algorithm based on association rule mining
Chanchal Yadav, Shuliang Wang, Manoj Kumar
Abstract
Chanchal Yadav, Shuliang Wang, Manoj Kumar
Abstract
Apriori algorithm is a popular and a classical algorithm in data mining. The main idea of this approach is to find a useful pattern in various sets of data. The algorithm suffers from many drawbacks. This paper deals with the apriori algorithm, and various techniques that were proposed to improve the apriori algorithm. The paper discusses about various approaches use to overcome the drawback of the apriori algorithm as to improve its efficiency. It also discusses about the new proposed model for improvement of apriori algorithm. The novel algorithm decreases pruning operation of candidate itemset. A new and improved model to handle dataset and to find an association between them is given. The new algorithm reduces storage space, improves efficiency and accuracy of the algorithm.
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Apriori algorithm is a popular and a classical algorithm in data mining. The main idea of this approach is to find a useful pattern in various sets of data. The algorithm suffers from many drawbacks. This paper deals with the apriori algorithm, and various techniques that were proposed to improve the apriori algorithm. The paper discusses about various approaches use to overcome the drawback of the apriori algorithm as to improve its efficiency. It also discusses about the new proposed model for improvement of apriori algorithm. The novel algorithm decreases pruning operation of candidate itemset. A new and improved model to handle dataset and to find an association between them is given. The new algorithm reduces storage space, improves efficiency and accuracy of the algorithm.
Key concepts: Apriori algorithm, Association rule learning, Computer science, GSP Algorithm, Pruning, Data mining, A priori and a posteriori, Algorithm