Classification method and system for non-equilibrium data sets in cerebral apoplexy

The invention discloses a classification method and system for non-equilibrium data sets in cerebral apoplexy. According to the method, a difference matrix is constructed by using an adaptive factor,and the influence of the imbalance of the number of cerebral apoplexy patient data and non-cerebral apoplexy patients in a cerebral apoplexy non-equilibrium data set on a classification result is fully considered, so an improved fuzzy membership function is more suitable for the classification of the cerebral apoplexy non-equilibrium data set; when the fuzzy membership function is constructed, theuncertainty of sample points is measured by utilizing information entropy according to the quantitative relation between different types of samples at first, and then an improved fuzzy membership function is constructed by considering the relationship of distances between similar samples; and the improved fuzzy membership function is applied to a fuzzy support vector machine, so the classification performance of a fuzzy s