摘要
通过研究各种决策树分类算法的并行方案后,并行设计C4.5算法。同时根据Hadoop云平台的MapReduce编程模型,详细描述C4.5并行算法在MapReduce编程模型下的实现及其执行流程。最后,对输入的海量文本数据进行分类,验证了算法的高效性和扩展性。
In this paper, a parallel C4.5 algorithm is put forward by the study of a variety of decision tree classification algo rithm parallel programs and the MapReduce programming model of the Hadoop cloud computing platform. At the same time, the ex ecution flow of the C4.5 parallel algorithms in the MapReduce programming model is introduced. Finally, the input of mass text da ta is classificated to verify the efficiency and scalability of the algorithm.
出处
《微型机与应用》
2013年第12期85-87,91,共4页
Microcomputer & Its Applications
基金
福建省科技计划重点项目(2011H0028)
