决策树和贝叶斯分类算法在学生专业录取数据中的应用研究  

Application of Decision Tree and Bayes Classification Algorithm in Student Enrollment Data

作　　者：黄雪华 HUANG Xuehua(School of Information and Electronic Engineer, Hurmn City University, Yiyang, Hunan 413000, China)

机构地区：[1]湖南城市学院信息与电子工程学院,湖南益阳413000

出　　处：《湖南城市学院学报（自然科学版）》2017年第4期64-67,共4页Journal of Hunan City University:Natural Science

摘　　要：分类算法是数据挖掘中最重要的挖掘理论之一,广泛应用于天气预测、反垃圾邮件、疾病诊断等应用中﹒通过介绍应用最广泛的两类分类算法决策树和贝叶斯理论及算法,并应用于湖南城市学院专业招生录取数据中,结合SQL server及ASP.NET,获取每个专业的学生性别预测,获取每个专业生源省份预测,并对预测结果和实际结果进行比较,得到误差率分别在0.01和0.2以内﹒Classification algorithm is one of the most important mining theories in data mining. It is widely used in weather forecasting, anti spam, disease diagnosis and other applications. The theory and algorithm of the most widely used decision tree and Bayes are introduced, and applied to student enrollment data of Hunan City University combining with SQL server and ASP.NET to get gender prediction for each major and predict the province students are from. Compare the predicted results with the actual results, it is found that the error rates are within 0.01 and 0.2 respectively.

关 键 词：分类 决策树 朴素贝叶斯 ASP.NET SQL Server2014 专业录取 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]