Thinking of College Students' innovation and Entrepreneurship Education under the background of big data

Abstract

In order to solve the problem of insufficient effectiveness of traditional college students' innovation and entrepreneurship education, this paper proposes a new method of College Students' innovation and Entrepreneurship Education under the background of big data. In order to achieve more effective innovation and entrepreneurship education of College Students under the background of big data, K-means clustering method is needed to deeply mine the innovation and entrepreneurship data of college students. Mining more accurate entrepreneurial data of college students, based on the above mining entrepreneurial data of college students as the basis of index construction, the maximum eigenvalue of College Students' entrepreneurial risk evaluation index is calculated, and the consistency test of evaluation index is completed according to the calculation results. According to the test results, calculate the correlation degree of College Students' entrepreneurial risk evaluation index, screen out the evaluation index of College Students' entrepreneurial risk, and construct the evaluation function of College Students' entrepreneurial risk according to the evaluation index. The experimental results show that, compared with the traditional methods, the proposed method can achieve higher accuracy of data mining for college students' entrepreneurship, and the risk evaluation results are more accurate.