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Received:April 01, 2013 Revised:May 02, 2013
Received:April 01, 2013 Revised:May 02, 2013
中文摘要: 本文通过数据挖掘对传统ID3决策树分类算法及性能进行分析研究, 利用高等数学中的微分理论知识, 改进和优化了ID3算法中的运算速度和选择测试属性偏向问题, 并进一步给出了改进算法的伪代码.
Abstract:This thesis analyzes the traditional ID3 decision tree classification algorithm and performance by using data mining, using the theory of differential knowledge in higher mathematics, improves and optimizes the operation speed and the test attribute selection bias problem in ID3 algorithm, and further gives the pseudo-code of the improved algorithm.
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基金项目:辽宁省教育科学“十二五”规划立项课题(JG12EB052)
引用文本：
罗雨滋,付兴宏.数据挖掘ID3决策树分类算法及其改进算法.计算机系统应用,2013,22(10):136-138,187
LUO Yu-Zi,FU Xing-Hong.Data Mining ID3 Decision Tree Classification Algorithm and its Improved Algorithm.COMPUTER SYSTEMS APPLICATIONS,2013,22(10):136-138,187
罗雨滋,付兴宏.数据挖掘ID3决策树分类算法及其改进算法.计算机系统应用,2013,22(10):136-138,187
LUO Yu-Zi,FU Xing-Hong.Data Mining ID3 Decision Tree Classification Algorithm and its Improved Algorithm.COMPUTER SYSTEMS APPLICATIONS,2013,22(10):136-138,187
