Comparative Study of COFI Tree and FP-Growth Algorithms for Association Rule Mining

Abstract

The issue of the mining association rule has pulled in a great deal of consideration in the exploration network. In the field of data mining, Frequent Pattern Mining is one of the principal classes of issues. Frequent Pattern Mining has been successfully applied to market basket analysis like diverse domains. This paper presents essential ideas of a portion of the algorithms (COFI-Tree, FP-Growth), where, FP-Tree like structure for mining the successive item-sets alongside their abilities and correlations. The experiment includes four different databases used for finding frequent datasets to measure a time complexity. The results show COFI-Tree takes less time to generate frequent pattern set mining.