基于混合贝叶斯网络数据挖掘及研究生升学预测模型的研究
PDF下载 (445)叶善文,赵杰煜.基于混合贝叶斯网络数据挖掘及研究生升学预测模型的研究[J].宁波大学学报(理工版),2013,26(03):40-44.DOI:
YE Shan-wen,ZHAO Jie-yu.Mass Data Mining and Graduate Prediction Model Construction Based on Cooperative Bayesian Network[J].Journal of Ningbo University(Natural Science & Engineering Edition),2013,26(03):40-44.DOI:
| Title: | Mass Data Mining and Graduate Prediction Model Construction Based on Cooperative Bayesian Network |
| 作者: | 叶善文, 赵杰煜 |
| Author(s): | YE Shan-wen, ZHAO Jie-yu |
| 关键词: | 贝叶斯网; 混合模型; 数据挖掘; 升学预测 |
| Keywords: | bayesian networks; cooperative model; data mining; examination predicting |
| 分类号: | TP302 |
| 文献标识码: | A |
| 摘要: | 给出了基于MAP和MDL混合机制的贝叶斯网络结构学习算法, 新算法吸取了两种方法各自的特点, 具有计算简单、收敛速度快且能综合利用先验知识及专家知识的优点. 并结合A校研究生的海量数据进行实验, 结果表明: 新的预测模型准确率可达84%, 且推理高效合理. |
| Abstract: | Based on the Maximum Aposterior Probability (MAP) and Minimum Description Length (MDL), this paper presents an algorithm of Bayesian networks structure learning. The algorithm effectively combines the characteristics of two methods, and takes the full advantage of simplistic computation, rapid convergence and priori knowledge and expert system. The experiment with mass data collected from a University graduate entrance examination shows that the model-based algorithm can efficiently be used for prediction and the success rate reaches 84%. |
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| 备注/Memo: | 收稿日期: 2013?03?15. 第一作者: 叶善文（1972－）, 男, 浙江江山人, 硕士/助理研究员, 主要研究方向: 人工智能及高校管理研究. E-mail: yeshanwen@nbu.edu.cn 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
