Based on the SVM University Education's Quality Regression Analysis

Due to the complexity of the quality control of higher education and its influence factors, it has always been difficult to have a control on the quality of higher education so as to realize the quantification analysis and give a prediction for the future quality. The ordinary ways of regression analysis have difficulty in establishing models and may lead to ¿over learning¿. The support vector machine (SVM) does not have a strict requirement on the number of samples, the distribution of process errors and sample points, and is easy to promote. In this paper, We make a SVM regression analysis of the quality control and prediction of higher education and put forward a regression model with strong generalization ability from the angle of machine learning. The results of the effect of fitting are good under the Kolmogorov-Smirnov (KS) test. Thus, the problems of establishing models, making quantification analysis in the quality control of higher education can have a solution.