research of improved fp-growth algorithm in association rules mining
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ID: 153090
2015
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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 algorithm is more than 1050 and N Painting-Growth algorithm is less than 10000 in data volume; the performance of the two kinds of improved algorithms is better than that of FP-Growth algorithm.
| Reference Key |
zeng2015scientificresearch
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|---|---|
| Authors | ;Yi Zeng;Shiqun Yin;Jiangyue Liu;Miao Zhang |
| Journal | environmental pollution |
| Year | 2015 |
| DOI |
10.1155/2015/910281
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| URL | |
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