概率频繁模式挖掘之U-apriori算法研究

不确定性数据的频繁项集挖掘的算法—U-apriori算法采用逐层迭代搜索方法,使用候选项集来找频繁项集.分析了U-apriori算法的流程和实现过程,并通过实验对比得出U-apriori算法花费较少时间和空间的优点,最后针对该算法的缺点提出了改进思路.结果表明：U-apriori算法是最佳概率频繁模式挖掘方法之一.

Research of U-apriori Algorithm on Excavation to Frequent Patterns of Probability

Uncertainty data＇ frequent item-sets excavation algorithm- U-apriori Algorithm adopts layer by layer and iteration method,which uses candidating item-sets to look for frequent item-sets.The article analyzes the process and realization of U-apriori Algorithm.By doing experiment and comparing,it conludes that U-apriori has the good point of less time and less space.The passage also points out some improving ways on the defects existed.The result is that U-apriori Algorithm is one of the best excavation ways of frequent patterns.