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作 者:曾小丽[1] 王中生[1] ZENG Xiao-li, WANG Zhong-sheng (School of Computer Science and Engineering, Xi' an Technological University, Xi'an 710032, China)
机构地区:[1]西安工业大学计算机科学与工程学院,陕西西安710032
出 处:《电脑知识与技术》2009年第9期7314-7317,共4页Computer Knowledge and Technology
摘 要:它概述了数据挖掘的几种常用算法,在权衡利弊的情况下,选择了决策树算法,它的优点是描述简单、分类速度快.特别适合大规模的数据处理,另外,以其易于提取显式规则、计算量相对较小、可以显示重要的决策属性和具有较高的分类准确率,综合以上优点及教学评估数据的结构化特性,选择分类技术中的决策树方法用于教学评估数据挖掘系统。In order to increase the processing technology of data complexity,the article provides an overview of several commonly used data mining algorithms, in weighing the pros and cons , then choose the decision tree algorithm, and its advantages are described in simple, classification speed, especially suitable for large-scale data processing, In addition, its ease of extraction of explicit rules for calculating the volume of relatively small, and they demonstrated the important decision-making attributes and classification with high accuracy, Taking all these advantages and the structuring characteristics of the evaluation data , select the decision tree method of the classification for teaching evaluation data mining system.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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