원문정보
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
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