Analysis Of The Relation Of College Students’ Learning And Employment Based On Classic Decision Tree Algorithm

In recent years, the expansion of colleges leads to the growing number of university graduates. So the employment situation becomes the primary problem. According to statistics, the number of college graduates of our country rise from3.38million in2005to6.99million in2013. In order to facilitate the management of students, colleges built the student management system and retain a lot of student data. Therefore, facing the difficult employment problem, policymakers want to know how to develop students to make their students easy to find an ideal job.Based on the students’data of the college of computer and information engineering, the paper analyzes three consecutive years of situation. First, the sample data were collected. Then the data was processed through a series of processes included integration, data scrubbing and transformation. Finally, considering the factors that affect the employment situation of university students, the paper adopts classical decision tree algorithm calculation to compare and analyze the situation of leaning in school and employment. The corresponding classification rules are obtained.This paper introduces in detail the concept and development history of decision tree algorithm in the data mining, analyzes three classical decision tree algorithms which include ID3,C4.5,CART algorithm. The three algorithms are used in students in school and courses and research the internal connection with them. Three algorithms make a comparison and analyze its merits and faults. Finally, according to the classification rules that are obtained by decision tree, the paper tests the rules of accuracy, as the same time finds a great influence on decision attribute between employment and management.We arrive at the conclusions after use above algorithm. The main factor of students’employment rate attribute is mainly about practical ability foreign language level and courses average grades.On the basis of attribute,university administrators can improve the employment rate and the existing training mechanisms.