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  • 标题:Improved Data Mining Algorithms Based on an Early Warning System of College Students
  • 本地全文:下载
  • 作者:Zhou, Lijuan ; Chen, Yuyan ; Li, Shuang
  • 期刊名称:Journal of Software
  • 印刷版ISSN:1796-217X
  • 出版年度:2013
  • 卷号:8
  • 期号:9
  • 页码:2352-2359
  • DOI:10.4304/jsw.8.9.2352-2359
  • 语种:English
  • 出版社:Academy Publisher
  • 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.
  • 关键词:Data Mining;Cluster Analysis;Association Rules;BP Neural Network
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