[1]潘大胜,屈迟文.一种改进ID3型决策树挖掘算法[J].华侨大学学报(自然科学版),2016,37(1):71-73.[doi:10.11830/ISSN.1000-5013.2016.01.0071]
 PAN Dasheng,QU Chiwen.An Improved ID3 Decision Tree Mining Algorithm[J].Journal of Huaqiao University(Natural Science),2016,37(1):71-73.[doi:10.11830/ISSN.1000-5013.2016.01.0071]
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一种改进ID3型决策树挖掘算法()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第37卷
期数:
2016年第1期
页码:
71-73
栏目:
出版日期:
2016-01-03

文章信息/Info

Title:
An Improved ID3 Decision Tree Mining Algorithm
文章编号:
1000-5013(2016)01-0071-03
作者:
潘大胜 屈迟文
百色学院 信息工程学院, 广西 百色 533000
Author(s):
PAN Dasheng QU Chiwen
School of Information Engineering, Baise University, Baise 533000, China
关键词:
数据挖掘 ID3型决策树 熵值计算 UCI数据集
Keywords:
data mining ID3 decision tree entropy calculation UCI data set
分类号:
TP301.6
DOI:
10.11830/ISSN.1000-5013.2016.01.0071
文献标志码:
A
摘要:
分析经典ID3型决策树挖掘算法中存在的问题,对其熵值计算过程进行改进,构建一种改进的ID3型决策树挖掘算法.重新设计决策树构建中的熵值计算过程,以获得具有全局最优的挖掘结果,并针对UCI数据集中的6类数据集展开挖掘实验.结果表明:改进后的挖掘算法在决策树构建的简洁程度和挖掘精度上,都明显优于ID3型决策树挖掘算法.
Abstract:
By analyzing the problem of ID3 decision tree mining algorithm, the entropy calculation process is improved, and a kind of improved ID3 decision tree mining algorithm is built. Entropy calculation process of decision tree is redesigned in order to obtain global optimal mining results. The mining experiments are carried out on the UCI data category 6 data set. Experimental results show that the improved mining algorithm is much better than the ID3 type decision tree mining algorithm in the compact degree and the accuracy of the decision tree construction.

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备注/Memo

备注/Memo:
收稿日期: 2015-11-13
通信作者: 潘大胜(1975-),男,副教授,主要从事数据挖掘技术的研究.E-mail:bspandsh@163.com.
基金项目: 广西自然科学基金青年基金资助项目(2014GXNSFBA118283)
更新日期/Last Update: 2016-01-20