分类是数据挖掘中重要的研究课题。文章介绍了SPRINT分类算法。为了提高该算法在海量数据库中分类的总体效率,笔者提出了两种处理离散属性的新方法,这些方法能明显减少求最佳分割点的运算量,提高算法的执行速度。
Classification is an important topic in the data mining research.We introduce SPRINT algorithm. To improve its overall efficiency of a classifier in very large databases,we present two new methods to process categorical attributes.With the help of methods,the SPRINT algorithm can reduce its operations to find the best splitting point,and get more efficient.