Implementation of Apriori algorithm, using C#. Apriori is a classic algorithm for learning association rules. Apriori is designed to operate on databases containing transactions (for example, collections of items bought by customers, or details o

AprioriAll算法的基本思路 1) 排序阶段 利用客户标识customer 2id作为主关键字以及事务发生的时间transaction 2 time作为次关键字对数据库D排序,该步骤将原始的事务数据库转换成客户序列的数据库. 2) 发现频繁项集阶段 利用关联规则挖掘算法找出所有的频繁项目集. 3) 转换阶段 在已经转换的客户序列中,每一个事务被包含于该事物中的所大项目集来替换,如果一个序列不包含任何大项目集,则在已经转换的序列中不应该保留这项事务. 4) 序列阶段 利用核心

Hidden Markov Models in C#-Introduction Hidden Markov Models were first described in a series of statistical papers by Leonard E. Baum and other authors in the second half of the 1960s. One of the first applications of HMMs was speech recognition,