Research of improved FP-growth algorithm in association rules mining

Abstract

Association rules mining is an important technology in data mining. FP-Growth (frequent-pattern growth) algorithm is a classical algorithm in association rules mining. But the FP-Growth algorithm in mining needs two times to scan database, which reduces the efficiency of algorithm. Through the study of association rules mining and FP-Growth algorithm, we worked out improved algorithms of FP-Growth algorithm-Painting-Growth algorithm and N (not) Painting-Growth algorithm (removes the painting steps, and uses another way to achieve).We compared two kinds of improved algorithms with FP-Growth algorithm. Experimental results show that Painting-Growth algorithmismore than 1050 andNPainting-Growth algorithmis less than 10000 in data volume; the performance of the two kinds of improved algorithms is better than that of FP-Growth algorithm.