Earticle

초록

영어

The percent of examinees’ first applications for a university can reflect the scientific research level of this university, so various universities start to research how to improve the percent of examinees’ first applications under the condition of not influencing the enrollment quality. For such research, C4.5 decision tree algorithm is applied to the postgraduate enrollment of a certain university. Specifically, examinees’ information is processed to select decision attributes and establish the decision tree so as to obtain the relation among examinees’ first applications, native place information, total points of initial examination and category of graduation universities from the rules extracted thereby. The mining result shows that this algorithm can correctly classify the graduation universities and assist the enrolling personnel to more effectively stipulate the enrollment guide for the targeted enrollment propaganda, thus to improve the percent of examinees’ first applications.

목차

Abstract
 1. Introduction
 2. C4.5 Algorithm Introduction
  2.1. C4.5 Algorithm
  2.2. Tree Pruning
 3. Decision Tree Establishment of C4.5 Algorithm
  3.1. Data Preprocessing
  3.2. Establishment of Decision Tree Model
  3.3. Classification Generation Rule
  3.4. Result Analysis
 4. Conclusion
 Acknowledgement
 References

키워드

저자

• Hu Xiaoyong [ Guiyang University, Guiyang Guizhou, 550005 China ]
• Yin Yujia [ Guiyang University, Guiyang Guizhou, 550005 China ]
• Wang Yuqian [ Guiyang University, Guiyang Guizhou, 550005 China ]
• Kang Le [ Guiyang University, Guiyang Guizhou, 550005 China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605