并行决策树算法的研究

Study in Parallel Algorithm for Decision Tree in Data Mining

数据挖掘在科研和商业应用中正发挥着越来越重要的作用。随着数据量的增加,数据挖掘工具处理海量数据的能力问题显得日益突出。研究并行算法,是解决这个问题的有效途径。分类器是数据挖掘的一种基本方法,决策树是一种最重要的分类器。文章首先介绍了分类器中的决策树算法,然后设计了一种并行决策树算法,最后探讨了该并行算法在PVM系统下的实现。

Data Mining plays an important role in scientific research fields and business applications.As the dataset's scale increases rapidly,the ability of dealing with mass-data becomes important.Parallel technology is an effective way to resolve this problem.Classification is one of the most important tasks of Data Mining,while decision tree is the most useful method in Classification.This article studies parallel algorithm for decision tree in Data Mining.Finally,an example of system built under PVM is introduced.