【摘要】 提出了一种区间值聚类的数据挖掘方法。该方法首先将数据库中的数据按照属性进行聚类,将它们划分为若干区间,对于同一区间中的数据赋予相同的编号,以此处理直至数据库的最后一个属性。在完成这种转换后即可使用关联规则的挖掘方法。该方法与传统的数据挖掘方法相比更加符合实际。大量的仿真数据集和真实数据集的实验结果表明该算法是有效的。更多还原

【Abstract】 A method of data mining based interval-values clustering is proposed. This kind of way is to cluster the data in a database by their attributes, and divides them into a certain intervals, to the data in the same interval we bestow them the same signal; by this way we accomplish the division for all the attributes in the database. After finishing the exchange we can mining it by the association rule mining method. This kind of method is more practical than the traditional way. Large quantity of simulative data and true data were tested to denote the valid of this method.更多还原