apriori(arules)
apriori()所属R语言包：arules
Mining Associations with Apriori
矿业协会的Apriori
译者：生物统计家园网 机器人LoveR
描述———-Description———-
Mine frequent itemsets, association rules or association hyperedges using the Apriori algorithm. The Apriori algorithm employs level-wise search for frequent itemsets. The implementation of Apriori used includes some improvements (e.g., a prefix tree and
item sorting).
矿山频繁项集，关联规则或团体使用Apriori算法的超边。 Apriori算法采用水平明智的搜索频繁项集。使用Apriori算法的实现，包括了一些改进（例如，前缀树和项目分类）。
用法———-Usage———-
apriori(data, parameter = NULL, appearance = NULL, control = NULL)
参数———-Arguments———-
参数：data
object of class transactions or any data structure which can be coerced into transactions (e.g., a binary matrix or data.frame).
对象类transactions或任何数据结构，可以将其强制transactions（例如，一个二进制矩阵或数据框）。
参数：parameter
object of class APparameter or named list. The default behavior is to mine rules with support 0.1, confidence 0.8, and maxlen 10.
对象的类APparameter或命名列表。默认的行为是挖掘规则，支持0.8，0.1，信心和MAXLEN 10。
参数：appearance
object of class APappearance or named list. With this argument item appearance can be restricted. By default all items can appear unrestricted.
对象的类APappearance或命名列表。使用该参数项目外观受到限制。默认情况下，所有项目都可以出现无限制的。
参数：control
object of class APcontrol or named list. Controls the performance of the mining algorithm (item sorting, etc.)
对象的类APcontrol或命名列表。控制性能的挖掘算法（项目排序，等等）
Details
详细信息———-Details———-
Calls the C implementation of the Apriori algorithm by Christian Borgelt for mining frequent itemsets, rules or hyperedges.
调用C语言实现的基督教Borgelt Apriori算法挖掘频繁项集，规则或超边。
Note: Apriori only creates rules with one item in the RHS (Consequent)!
注：Apriori算法只创建一个项目规则的RHS（因之）！
Note: The default value in APparameter for minlen is 1. This means that rules with only one item (i.e., an empty antecedent/LHS) like
注：中的默认值APparameterminlen是1。这意味着，只有一个项目的规则（即一个空的先行/ LHS）如
will be created. These rules mean that no matter what other items are involved the item in the RHS will appear with the probability given by the rule’s confidence (which equals the support). If you want to avoid these rules then use the argument parameter=list(minlen=2).
将被创建。这些规则意味着，无论什么其他项目所涉及的项目在RHS中会出现的概率规则的信心（相等于支持）。如果你想避免这些规则，然后使用参数parameter=list(minlen=2)。
值———-Value———-
Returns an object of class rules or itemsets.
返回对象类rules或itemsets。
参考文献———-References———-
between sets of items in large databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 207–216, Washington D.C.
Apriori Implementation. 15th Conference on Computational Statistics (COMPSTAT 2002, Berlin, Germany) Physica Verlag, Heidelberg, Germany.
Eclat. Workshop of Frequent Item Set Mining Implementations (FIMI 2003, Melbourne, FL, USA).
参见———-See Also———-
APparameter-class, APcontrol-class, APappearance-class, transactions-class, itemsets-class, rules-class
APparameter-class，APcontrol-class，APappearance-class，transactions-class，itemsets-class，rules-class
实例———-Examples———-
data("Adult")
## Mine association rules.[矿的关联规则。]
rules <- apriori(Adult,
parameter = list(supp = 0.5, conf = 0.9,
target = "rules"))
summary(rules)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
