基于分区的改进Apriori算法

分析了Apriori算法存在之不足，在此基础上提出了一种基于分区思想的IABP算法．该算法首先将待挖掘的数据集分成若干块，然后分别对各块进行挖掘．在挖掘过程中，只存储满足最小支持度的频繁项，并删除不满足最小支持度的非频繁项．测试结果表明，该挖掘方法降低了挖掘算法的时闻复杂度，提高了挖掘算法的效率．

An Improved Apriori Based on Partitions

Basing on the disadvantages of the Apriori algorithm being analyzed, an improved apriori algorithm based on partition is proposed in this paper. In this algorithm, the dataset which is waiting for mining is first parted into some partitions, and then each parttition is mined by using parallel operation. During the procedure of mining, only the frequently items which is satisfied the condition of minimal-support are stored in the memory, and the non-frequently items which don＇ t satisfy the condition of minimal-support will be deleted at the same time. The test result shows that this algorithm can decrease the time complexity of mining and increase the mining efficiency.