An approach to improve the efficiency of apriori algorithm
CSE Department, SGT Institute of Engineering & Technology, Gurgaon, India
- Published
- Accepted
- Subject Areas
- Algorithms and Analysis of Algorithms, Data Mining and Machine Learning
- Keywords
- Apriori algorithm, Support, Association rules, Frequent Itemset, Candidate Item Sets
- Copyright
- © 2015 Aggarwal et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. An approach to improve the efficiency of apriori algorithm. PeerJ PrePrints 3:e1159v1 https://doi.org/10.7287/peerj.preprints.1159v1
Abstract
Association rule mining has a great importance in data mining. Apriori is the key algorithm in association rule mining. Many approaches are proposed in past to improve Apriori but the core concept of the algorithm is same i.e. support and confidence of item sets and previous studies finds that classical Apriori is inefficient due to many scans on database. In this paper, we are proposing a method to improve Apriori algorithm efficiency by reducing the database size as well as reducing the time wasted on scanning the transactions.
Author Comment
This is a research article in field of association rule mining. Work is done to improve Apriori algorithm.