SVM-based Cancer Incidence Forecasting of Patients

As one of the machine learning methods that has been widely used in recent years, SVM can be applied to pattern classification and nonlinear regression. This paper proposes the basic modeling process by using SVM, and introduces the processing technique of dimension reduction by using MATLAB and principal component analysis method, and provides the process of classification forecasting by using SVM taking a data set of cancer patients as an example. Experiments show that the method is simple, easy to use and effective.