Improved data mining algorithms based on an early warning system of college students

被引：1

作者：

机构：

[1] Department of Information Engineering College, Capital Normal University, Beijing

[2] Capital Normal University, Information Engineering College, Beijing

来源：

| 1600年 / Academy Publisher卷 / 08期

关键词：

Association Rules; BP Neural Network; Cluster Analysis; Data Mining;

D O I：

10.4304/jsw.8.9.2352-2359

中图分类号：

学科分类号：

摘要：

In order to solve the problem of early warning of college students' achievement, this paper proposes two improved algorithms for data pre-processing and mining warning factor. At first we put forward an improved K-Means algorithm which is not only ensures the accuracy of the original algorithm, but also improves the stability of the algorithm. Then we put forward an improved algorithm New_Apriori algorithm and analyze experiment result. The result shows that the amount of data access has been reduced significantly and efficiency has been improved. In the end of this paper, we built the early warning model of students' achievement based on neural network. The result of experiment shows that the new algorithms improve the efficiency and accuracy of the early warning. © 2013 ACADEMY PUBLISHER.

引用

页码：2352 / 2359

页数：7

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