基于频繁模式树的普遍化关联规则挖掘

Mining Generalized Association Rules Based on Frequent Pattern Tree

提出了基于频繁模式树的普遍化关联规则挖掘算法 MGAR- FP,充分利用频繁模式树的性质 ,避免大量候选模式的生成和频繁模式匹配 ,提高了挖掘的效率和速度 .实验表明 ,算法是有效的 ,比传统的普遍化关联规则挖掘算法Cum

The algorithm MGAR-FP for mining generalized association rules based on frequent pattern tree is proposed. It makes full use of the properties of frequent pattern tree and avoids producing a large number of candidate itemsets, so speeding up the mining. The experiments shows it is efficient and it's execution speed is faster than the traditional mining algorithm Cumulate.