计算机技术与发展2016，Vol.26Issue(4)：114-118,5.DOI:10.3969/j.issn.1673-629X.2016.04.025
贝叶斯决策树方法在招生数据挖掘中的应用
Application of Bayesian Decision Tree Method in Admission Data Mining
摘要
Abstract
It simply introduces the basic thought of Bayesian decision tree method in this paper,which takes advantage of the prior infor-mation method for Bayesian classification and the information gain method of decision tree,and makes up for the decision tree cannot handle the ambiguity data and the missing value by adding Bayesian node. On this basis, a Bayesian decision tree algorithm based on Naïve Bayesian method and ID3 algorithm is presented named NBDT-ID3 algorithm. The algorithm process of the design and analysis is introduced. Then the algorithm is applied to higher vocational admission data mining,which analyzes and forecasts the new student regis-tration. It is tested and verified under the Matlab environment. The experimental results show that NBDT-ID3 algorithm not only can get higher classification accuracy but also behave well in handling the ambiguity,incomplete or incongruous data in the case of paying certain of time.关键词
数据挖掘/贝叶斯决策树/分类/招生数据/报到预测Key words
data mining/Bayesian decision tree/classification/admission data/registration forecasting分类
信息技术与安全科学引用本文复制引用
黄春华,陈忠伟,李石君..贝叶斯决策树方法在招生数据挖掘中的应用[J].计算机技术与发展,2016,26(4):114-118,5.基金项目
中央高校基本科研业务费专项基金项目(2042014f0057) （2042014f0057）
湖北省自然科学基金项目(2014CFB289) （2014CFB289）
