说明：  Apriori算法用于发现数据中的频繁项集以及关联规则，属于关联分析， 关联分析的目标包含两条：发现频繁项集和发现关联规则。 该算法基于一个很重要的原理，apriori原理，如果某个相机是频繁的，那么他的所有子集也是频繁的， 也就说，如果一个项集是非频繁的，那么它的所有超集也是非频繁的。 Apriori算法是先生成C1->L1->C2->L2->C3.Apriori算法的缺点是很明显的，每生成一个频繁项集，都要扫描整个数据集。 在数据规模很大的时候，这个是致命的性能瓶颈。
(Apriori algorithm is used to find data itemsets and association rules, are associated with analysis, Association analysis included two goals: find frequent itemsets and association rules discovery. The algorithm is based on a very important principle, apriori theory, if a camera is frequent, then all subsets also his frequent, Also said that if a non-frequent item sets, then it is also a superset of all the non-frequent. Apriori algorithm is Mr. Cheng C1-> L1-> C2-> L2-> shortcomings C3.Apriori algorithm is obvious, each generating a frequent item sets, must scan the entire data set. When a large-scale data, this is the fatal performance bottleneck.)