The main idea of SVM used for classifying nonlinear separable data is to map the data into higher dimension linear space in which the data can be separated by a hyper plane.Based on Jordan Curve Theorem

a universal classification method based on hyper surface

which is called HSC classification

is put forward in this paper.The classification hyper surface is directly made to classify massive data according to whether the wind number is odd or even.It is a novel approach that does not need to make mapping from lower dimension space to higher dimension space and considering kernel function too.It can directly solve the nonlinear multiclasses classifying problem.The test reports show that HSC can efficiently and accurately classify large data.