摘要
在对关联规则挖掘算法Apriori进行深入研究的基础上,提出了一种采用频繁项集Lk-1与L1连接生成候选项集Ck的思想,并基于这种新的思想提出了一种优化的算法1-K_Apriori算法.在真实数据集和实验数据集上所做的实验及结果表明,1-K_Apriori算法是有效的.
After studying and discussing the algorithm of Apriori on association rule mining,authors point out the disadvantage of Apriori algorithm and present an improved algorithm,1-K_Apriori.In 1-K_Apriori algorithm the candidate C_k is generated as a join between frequent itemsets L_(k-1) and L_1.The experiments show that the 1-K_Apriori algorithm is high efficiency.
出处
《沈阳理工大学学报》
CAS
2006年第1期40-42,共3页
Journal of Shenyang Ligong University
