Abstract

In Data Mining, Association Rule Mining is a standard and well researched technique for locating fascinating relations between variables in large databases. Association rule is used as a precursor to different Data Mining techniques like classification, clustering and prediction. The aim of the paper is to guage the performance of the Apriori algorithm and Frequent Pattern (FP) growth algorithm by comparing their capabilities. The evaluation study shows that the FP-growth algorithm is efficient and ascendable than the Apriori algorithm.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.