Abstract:Currently, the great changes of higher education development h ave taken place in the internal and external conditions, in the continuous i mprove the quality of higher education is the main melody of higher educ ation reform and development. Higher education is important to the talent pool,and researching the main factors that affect the quality of higher ed ucation, as well as the degree of influence is becoming the top priority to ensure the improvement of higher education.In the past, when researching the quality of higher education, the majority of scholars are doing qualit ative analysis with little or no quantitative analysis, it’s difficult to make a scientific system of quality control of higher education research metho-ds.In view of this, this paper attempts to make a quantitative analysis on the quality of higher education in China, from a mathematical point of vi-ew.Firstly, with a lot of literature to read and analyze.sumarizing the fi-ve categories resources which affecting on the quality of our higher educa tion (school funds, school facilities, teachers, students’quality and the sci-entific research conditions).we used principal component analysis of the main factors of the five categories of resources on indicators screening to find the ten key component,then two kind of cluster analysis was done on these key component to study the differences between the various regions;Doing the regression analysis of factors affecting the quality of China’s h igher education with the SVM technology,proposed a regression model w ith a high generalization ability from the view of machine learning,and ob tained the fitting function about the factors affecting the quality of higher education as well as the size of these various factors. At the end of this ar-ticle,by a combination of qualitative and quantitative analysis, propose th e policy recommendations of how to use existing resources to improve th e quality of higher education in China.In this article, there are9pictures,23figures and64references in total. |