Research of Improved FP-Growth Algorithm in Association Rules Mining

[摘要] 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 improvedalgorithms 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 algorithmswith FP-Growth algorithm. Experimental results show that Painting-Growth algorithm is more than 1050 and NPainting-Growth algorithmis less than 10000 in data volume; the performance of the two kinds of improvedalgorithms is better than that of FP-Growth algorithm.

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