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.