基于Aprior&FP-growth算法的研究

Research Based on Aprior & FP-growth Algorithm

关联规则挖掘在数据挖掘中占有极其重要的地位,Apriori算法和FP-growth算法是当前关联规则中两大主要频繁项集发现算法.研究了这两种算法的基本思想,指出了算法各自的优缺点并通过具体的实例说明发现频繁项集的方法,最后通过实验对算法进行了性能上的比较.

Mining of association rules in data mining plays an important role, Apriori algorithm and FP-growth algorithm are the two major association rules frequent itemsets discovery algorithm.study of the two kinds of the basic idea of the algorithm, points out the advantages and disadvantages of the algorithm through specific examples of frequent itemsets found method, finally through the experiment to the algorithm for the performance comparison.